security configurationsMinimum of 2 years experience developing business rules in VB.net or C#Minimum of 2 years experience developing Data Management sequences and stepsMinimum of 3 years report & dashboard developmentM…
Engineering & IT · Miami, FL
Data Engineer jobs in Miami, FL
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.
174
Open roles today
$41–$103/hr
Typical pay range
$142k
Median, full-time
5
Fresh in this list
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01
Open data engineer roles
12 shown of 174 · sorted by freshness
Managing Director, Data Engineering & AIWho You'll Work WithAs a Managing Director in Slalom's Data & AI practice, you will lead the growth of our Data Engineering & AI business by helping clients modernize their data fo…
DescriptionJob SummaryThe Supply Chain Systems & Data Governance Analyst plays a vital role in maintaining and optimizing the item master data that powers critical supply chain operations across the health system. Direct…
processes that run it. That work changes the operating model an engineering organization runs on, the ways of working underneath it, and... ...We combine our strength in technology and leadership in cloud, data and AI wi…
$110.7k - $218.3k
across personas such as Field Sales, KAM, MSLs, or Field Reimbursement ManagersExperience with adjacent Salesforce products such as Data Cloud, Experience Cloud, or MuleSoft based integrationsExperience delivering in a S…
Seeking an experienced Oracle OBIEE / OAS Data Engineer with strong expertise in Oracle Analytics Server, Oracle Database, SQL/PL/SQL, ETL, and Data Warehousing. The ideal candidate will be responsible for developing and…
Analytics Engineer Location: On-Site Miami · Reports to: Director, Data & Analytics · Department: Data & Analytics About eMed eMed is a leading digital health company specializing in cardio metabolic health through manag…
develop a talented workforce to create and deliver a wide range of content reflecting our world. Job Description The Data Engineering Manager will be a hands-on data engineering role supporting Universal+, Hayu, and the…
Zemsania busca Data Engineer Acerca de Zemsania: En Zemsania, somos líderes en la transformación digital, impulsando el éxito de nuestros clientes a través de soluciones tecnológicas innovadoras y de vanguardia. Contamos…
We are seeking an experienced Azure SQL Database Administrator (Azure SQL DBA) to manage, optimize, and support enterprise database environments. The role requires strong expertise in Azure SQL Database, Microsoft SQL Se…
technical excellence, ownership, proactive communication, and collaboration. About the Role We are looking for a Senior Data Platform Engineer to join a high-impact engagement with one of our partners, a global leader in…
seeking an experienced IT End User Analyst to provide L1/L2 desktop and end-user support, manage ServiceNow tickets, analyze IT support data, and assist with asset management and reporting. Roles and Responsibilities Pro…
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What data engineers earn in Miami
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $41–$57 | $86k–$119k |
| Mid level | $57–$79 | $119k–$165k |
| Senior | $77–$103 | $160k–$215k |
Adjusted for the Miami 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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