As a Software Engineer at National Fuel Gas, you will play a pivotal role in maintaining the digital backbone of a diversified energy company. This position is not merely about writing code; it is about building and sustaining the robust, data-driven systems that support natural gas storage, transmission, and utility operations. You will contribute to mission-critical infrastructure that ensures operational efficiency and regulatory compliance across the organization. The work is defined by its complexity and its direct impact on energy distribution. Whether you are working on ORACLE database architecture or supporting specialized engineering and geological software, your contributions ensure that data flows accurately and securely. You will operate at the intersection of traditional utility operations and modern software development, making this an ideal role for engineers who value stability, deep domain expertise, and long-term technical growth. ##### Tip The role often requires a blend of technical depth in database management and a willingness to understand the specific operational workflows of the energy sector.
Initial Screening
reportedAn initial assessment to gauge your background and interest in the position.
What to demonstrate
- An initial assessment to gauge your background and interest in the position
- Depth in Oracle SQL
How to prepare
- Be able to walk your CV end to end in two minutes, and say why this company specifically.
- Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Technical Interviews
reportedInterviews with technical leads focusing on your technical fit for specific projects.
What to demonstrate
- Interviews with technical leads focusing on your technical fit for specific projects
- Depth in Oracle SQL
How to prepare
- Answer aloud and timed: How do you approach debugging a performance bottleneck in a production database?
- Answer aloud and timed: What is your process for ensuring data integrity during schema migrations?
Behavioral Discussions
reportedConversations that evaluate how you operate within a team and your past project experiences.
What to demonstrate
- Conversations that evaluate how you operate within a team and your past project experiences
- Depth in Oracle SQL
How to prepare
- Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
- Re-read the description of the behavioral discussions above and write down what you would ask to confirm before it.
Department Management Interview
reportedPotential interviews with department management to assess long-term compatibility with company culture.
What to demonstrate
- Potential interviews with department management to assess long-term compatibility with company culture
- Depth in Oracle SQL
How to prepare
- Answer aloud and timed: How do you prioritize tasks when supporting multiple business units or competing project deadlines?
- Answer aloud and timed: Describe your approach to working within a team that relies on legacy systems alongside modern updates.
PracHub editorial advice for the preparation topics above.
Focus on SQL
Since many roles involve ORACLE, ensure your SQL skills are sharp; be prepared to write queries on a whiteboard or during a live coding session.
Know your projects
Be ready to talk about the "why" behind your past technical choices, especially when you had to make a trade-off between speed and stability.
Research the industry
Understanding the basics of natural gas storage or utility operations will give you a significant advantage in showing why you want to work at National Fuel Gas.
Be clear and concise
In both behavioral and technical answers, structure your response using the STAR method (Situation, Task, Action, Result) to keep your points impactful.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Identify the heaviest tenants in a five-minute window under memory pressure
The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.
Approach
- Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
- Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
- State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
- Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.
Follow-up
- The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
- Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?
Archive a resource graph without breaking live references or recursing
Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.
Approach
- Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
- Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
- Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
- Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.
Follow-up
- The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
- The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?
Diff a projection against the primary without per-row point reads
The listing projection has drifted and some rows show a stale version. The primary holds 40,000,000 resource rows across 12,000 tenants while serving 1,200 writes and 14,000 reads per second. The obvious repair, reading each resource row and comparing its version against the projection, is correct and would eventually finish. Explain precisely why it is unacceptable here, then give a diff that finds the differing rows, state its complexity, and make it safe to run against a live primary. Replication lag is usually under 100 ms and is not bounded.
Approach
- Quantify the naive cost rather than calling it slow: 40,000,000 point reads at even 0.5 ms each is over five hours serialised, and the only lever is concurrency, which is exactly what you cannot spend. The primary's pool is sized for the write path, and 40,000,000 random reads evict the buffer cache that sustains the 85 percent cache hit rate, so the audit degrades the system it is auditing.
- Replace random access with one ordered pass per side. Both sides can be read in (tenant_id, resource_id) order, which is a sequential scan on each and a merge join in O(n) time and O(1) memory. For a dense diff that is the whole answer, and it reads the primary once instead of 40,000,000 times.
- For the expected sparse case, compare range hashes instead of rows: partition the key space, compute per range an order-independent aggregate over hash(resource_id, version), compare aggregates, and descend only into ranges that differ. With d differing rows and branching factor B, at most d ranges mismatch per level, so the drill-down examines O(d log_B(n/d)) ranges and reads full rows only in mismatching leaves.
- Aggregate with a sum modulo 2^64 or a multiset hash, never XOR. XOR is order-independent but self-cancelling, so two rows wrong in the same way, or a row duplicated on one side, leave the range aggregate matching and the range is declared clean.
Follow-up
- The diff reports 900 stale rows. How do you decide between patching those rows and rebuilding the projection from resource_revision?
- Same job, but the projection lives in a search index that cannot be scanned in key order. What changes?
How do you optimize complex SQL queries for large datasets?
How do you optimize complex SQL queries for large datasets?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
Explain the difference between various join types and when to use them for efficiency.
Explain the difference between various join types and when to use them for efficiency.
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
What is your process for ensuring data integrity during schema migrations?
What is your process for ensuring data integrity during schema migrations?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Choose what to break when replication lag reaches forty seconds
Reads are served from two replicas: 14k requests/second, about 85% absorbed by cache, so roughly 2.1k reads/second reach the database. Writes go to the primary at 1.2k/second. A tenant's backfill drives replication lag from under 100 ms to 40 seconds and it is still climbing. Sessions that have just written are pinned to the primary. Decide, endpoint class by endpoint class, whether to serve stale, fail, or route to the primary, and justify each choice with the load it adds to the primary. Then state what you would have built beforehand.
Approach
- Establish blast radius before cause, because mitigation and diagnosis have different deadlines. The decisive arithmetic is what happens if the database reads move to the primary: 2.1k reads/second on top of 1.2k writes/second roughly triples its operation count, on the node already absorbing the backfill that caused this. Reads and writes are not equal in cost, so treat that as an argument against a blanket move rather than as a capacity model - but it is enough to rule out routing everything to the primary.
- Classify endpoints by what staleness costs, not by how important they feel. Reads whose staleness is invisible - listings, search, counters - stay on the replica and return the watermark so the client can tell. Reads that immediately follow that same session's write keep their primary pin, which is a small bounded slice of traffic rather than the whole 2.1k/second. Reads that feed a decision with a side effect - authorisation, quota, the read half of a read-modify-write - must not be stale at all, because a 40-second-old permission row is the stale-permission failure wearing a different costume; those go to the primary or fail.
- Shed instead of queueing. If the must-be-fresh class alone exceeds the primary's headroom, refuse its lowest-value slice with 503 and a retry-after. A request queued behind a saturated primary holds a connection for a client that has already given up, and the retry storm that follows is what turns degradation into an outage. Bound the connection pool per role so the read fallback cannot consume the write path's connections - that bulkhead is the single decision that determines whether writes survive the next ten minutes.
- Attack the cause in parallel, since it is the one thing that can be stopped. The backfill is the load generator. A backfill that reads replication lag as its throttle signal and pauses above a threshold would have made this a non-event, with batch sizes small enough that each batch's write volume is a fraction of what a replica can apply per second. That is most of the answer to what should have existed beforehand.
Follow-up
- Lag returns to normal in nine minutes. Which mitigation do you remove first, and which one stays permanently?
- A user reports their change did not save, and the write committed. Trace the path that produces that report and name the signal that would have shown it before the report arrived.
How do you approach debugging a performance bottleneck in a production database?
How do you approach debugging a performance bottleneck in a production database?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Built from the rounds and topics National Fuel Gas candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the National Fuel Gas loop
- Write out the reported sequence: Initial Screening, Technical Interviews, Behavioral Discussions, Department Management Interview.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.
02Work Oracle SQL
- Spend the session on Oracle SQL, which National Fuel Gas candidates report being tested on.
- Write one worked example in Oracle SQL and time yourself on it.
Deliverable: One timed worked example in Oracle SQL.
03Work PL/SQL
- Spend the session on PL/SQL, which National Fuel Gas candidates report being tested on.
- Write one worked example in PL/SQL and time yourself on it.
Deliverable: One timed worked example in PL/SQL.
04Work Oracle Database Administration Concepts
- Spend the session on Oracle Database Administration Concepts, which National Fuel Gas candidates report being tested on.
- Write one worked example in Oracle Database Administration Concepts and time yourself on it.
Deliverable: One timed worked example in Oracle Database Administration Concepts.
05Answer out loud: Technical & Database Proficiency
- Answer aloud, timed: How do you optimize complex SQL queries for large datasets?
- Answer aloud, timed: Describe your experience with ORACLE development tools and stored procedures.
Deliverable: Spoken answers to 2 reported Technical & Database Proficiency question(s), under time.
06Answer out loud: Behavioral & Professional Alignment
- Answer aloud, timed: Can you describe a time you had to explain a complex technical issue to a non-technical stakeholder?
- Answer aloud, timed: How do you prioritize tasks when supporting multiple business units or competing project deadlines?
Deliverable: Spoken answers to 2 reported Behavioral & Professional Alignment question(s), under time.
07Dry run for National Fuel Gas
- Run one full mock under time, then write down the two questions you most want to ask your interviewers.
Deliverable: A completed timed mock and two questions to ask.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Describe your experience with ORACLE development tools and stored procedures.
Describe your experience with ORACLE development tools and stored procedures.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Can you describe a time you had to explain a complex technical issue to a non-technical stakeholder?
Can you describe a time you had to explain a complex technical issue to a non-technical stakeholder?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you prioritize tasks when supporting multiple business units or competing project deadlines?
How do you prioritize tasks when supporting multiple business units or competing project deadlines?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Describe your approach to working within a team that relies on legacy systems alongside modern updates.
Describe your approach to working within a team that relies on legacy systems alongside modern updates.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Tell us about a time you identified a process improvement that saved time or resources.
Tell us about a time you identified a process improvement that saved time or resources.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you handle feedback on your code or architectural designs?
How do you handle feedback on your code or architectural designs?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
- 01
Describe your experience with ORACLE development tools and stored procedures.
- 02
Can you describe a time you had to explain a complex technical issue to a non-technical stakeholder?
- 03
How do you prioritize tasks when supporting multiple business units or competing project deadlines?
- 04
Describe your approach to working within a team that relies on legacy systems alongside modern updates.
How difficult are the technical interviews?
The technical interviews are rigorous but fair, focusing on practical application rather than theoretical puzzles. They test your ability to handle real-world problems you would encounter in the role, specifically regarding ORACLE and SQL.
National Fuel Gas Software Engineer candidate reports ↗What is the company culture like?
National Fuel Gas fosters a professional, stable, and collaborative environment. Employees are expected to be diligent, detail-oriented, and focused on the long-term success of the company’s infrastructure.
National Fuel Gas Software Engineer candidate reports ↗How long does the process take?
The timeline can vary based on the specific team and location, but it typically moves at a steady, professional pace. You can expect multiple stages including a screening and technical interviews with your potential peers and managers.
National Fuel Gas Software Engineer candidate reports ↗Is remote work common?
National Fuel Gas typically maintains a professional office-based culture, though specific policies may depend on the department and the nature of the role. Be sure to clarify expectations during your initial recruiter conversation.
National Fuel Gas Software Engineer candidate reports ↗What topics does National Fuel Gas test in interviews?
National Fuel Gas interviews most often cover Oracle SQL, PL/SQL, Oracle Database Administration Concepts, Stored Procedures, and Performance Tuning (SQL/PLSQL). The exact emphasis depends on the specific role you apply for.
National Fuel Gas Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01National Fuel Gas Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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