Senior Data Engineer - Philadelphia, 19109, United States of America How we LEAD: We are seeking an experienced and driven Senior Data Engineer Enterprise Data Products within the Global Data & Analytics team. You are pa…
Engineering & IT · Philadelphia, PA
Data Engineer jobs in Philadelphia, PA
Data engineers build the pipelines and warehouses that move data from source systems to the people and models that need it, keeping it fresh, correct, and queryable at scale.
203
Open roles today
$40–$101/hr
Typical pay range
$139k
Median, full-time
6
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01
Open data engineer roles
11 shown of 203 · sorted by freshness
working world. Manager - Financial Services Organization – AI and Data - Service Delivery Center EY is the only professional... ...Minimum of 5 years of related work experience in AI/ML engineering or MLE/ML Ops Experien…
$150k - $160k
Job Description The Director, Data Engineering & AI Enablement is the senior-most technical leader and active builder for the data engineering and artificial intelligence capability supporting the Facilities Management l…
$132.9k - $182.7k
evolve, grow, and succeed – today and into tomorrow. As an Electrical Engineer in our Advanced Manufacturing group, you’ll contribute to projects that enable the heart of our clients’ successful data center facilities en…
$123.6k - $162.3k
facilities; it’s about well-designed strategies tailored for every and every location. We're looking for a high-energy, Plumbing Engineer to join our Building Mechanical team and help deliver innovative Plumbing design s…
$169.5k - $233k
push boundaries, elevate standards, and deliver with purpose. As a senior subject matter expert within our Data Center team, you’ll lead structural engineering efforts across a portfolio of data center projects, includin…
Role: Data Operations Engineer / DataOps Specialist Skills: Digital : Python Experience Required: 10+ years Primary Skill: LangChain, LangGraph, VectorDB, Python, LLM's Secondary skill: Pl-SQL with ETL tools Big Data too…
Role Descriptions: 1. Data Pipeline & Operations Build, manage, and monitor ETL/ELT pipelines for data ingestion and transformation Ensure smooth data flow across systems, warehouses, and applications Automate workflows…
$132.9k - $182.7k
will be near a JACOBS U.S. based office, but we intend to hire the "best" candidates. We're looking for a Senior Civil Engineer to join our Data Center group, and you'll have the chance to work on projects including stat…
$100k - $130k
possible. To achieve this vision, Aramark will deliver strategic data assets that enable our operators to maximize the hospitality... ...experience for our consumer and clients. We are seeking a Data Engineer who will wo…
Senior Analyst - Financial Services Organization – AI and Data – Service Delivery Center EY is the only professional services... ...(trading, risk, compliance, or banking) Knowledge of prompt engineering and in-context l…
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What data engineers earn in Philadelphia
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $40–$56 | $84k–$117k |
| Mid level | $56–$78 | $117k–$162k |
| Senior | $75–$101 | $157k–$211k |
Adjusted for the Philadelphia market from national ranges.
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What employers ask for
The skills these listings keep naming
SQL and data modelingPython or ScalaAirflow or similar orchestrationSpark or other batch processingWarehouses (Snowflake, BigQuery)dbtStreaming (Kafka)Data quality testingCloud infrastructure
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Design a pipeline that loads data from a production database into a warehouse daily.
Cover extraction strategy, incremental loads versus full refresh, idempotency, and monitoring. Saying how you would backfill after a failure shows real pipeline experience.
How do you handle late-arriving or duplicate data?
Discuss idempotent upserts, watermarks, and dedup keys. This is a daily reality of the job, so a concrete example lands well.
Batch or streaming — how do you decide?
Anchor on the actual freshness requirement and cost. Most 'real-time' asks are fine at minutes; recognizing that is the mature answer.
A stakeholder says the numbers in their dashboard are wrong. Walk me through your debugging.
Trace lineage from the dashboard back to the source, isolating which layer diverged. Showing calm, structured lineage-tracing is the point of the question.
How do you model data for analytics — star schema, wide tables, something else?
Show you know the classic patterns and modern warehouse economics, and that you choose based on query patterns and team skill, not doctrine.
How do you test data pipelines?
Talk about schema and freshness checks, row-count and distribution tests, and tools like dbt tests or Great Expectations — plus alerting when they fail.
Tell me about a pipeline that failed badly and what you changed.
Structure it like an incident review: impact, cause, fix, prevention. Emphasize the durable improvement, such as monitoring or contract enforcement.
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Resume tips that move the needle
For data engineers specifically — generic advice costs you here
01
State data scale plainly — rows per day, terabytes managed, pipeline counts — because it is the first thing hiring managers scan for.
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Name your orchestration, processing, and warehouse tools per role; the modern stack (Airflow, dbt, Snowflake) is a keyword screen.
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Highlight reliability outcomes: pipeline failure rates, data freshness SLAs met, incident reductions.
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Show cost work if you have it — warehouse spend is a live concern and optimization stories differentiate.
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Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.
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Where this role goes
Typical progression
01
Junior Data Engineer
02
Data Engineer
03
Senior Data Engineer
04
Staff Data Engineer
05
Data Platform Lead
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