Data Engineer (Hybrid)

T M FLOYD & CO

Richmond, VA, United States

26 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Compensation

$130,146.0

Working hours

Regular working hours

Job source

www2.jobdiva.com

Tech stack

Artificial Intelligence Information Systems Continuous Integration Extract Transform Load (ETL) Data Warehousing DataOps SQL Databases Information Technology Low Latency Real Time Data Apache Kafka Spark Streaming

+2 more

Software Coding Data Pipelines

Job description

Build end-to-end data pipelines and ETL/ELT solutions to support analytics, reporting, and AI/ML use cases ensuring solutions are robust and production-ready through practical implementation
Apply scalable patterns for batch and incremental processing by developing, testing, and deploying data workflows focusing on hands-on coding and troubleshooting
Review and implement data modeling, transformation logic, and performance strategies using deep technical expertise to optimize and validate solutions
Evaluate, select, and integrate tooling, frameworks, and platform capabilities by actively prototyping and configuring systems to meet project requirements
Build up complex, high-volume data pipelines using SQL-centric ETL/ELT patterns
Design and implement scalable streaming pipelines to process real-time data ensuring low latency and reliable delivery for analytics and operational use cases
Build and maintain scalable, low-latency streaming data pipelines using technologies such as Kafka, Kinesis, or Spark Streaming

Requirements

5-7 years of data engineering experience
Advanced expertise in SQL, ELT patterns, and performance tuning
Strong experience with Oracle Exadata, Snowflake or similar cloud/on-prem data warehouses
Hands-on experience with enterprise ETL/ELT platforms (e.g., Talend, dbt, Informatica)
Deep understanding of data warehousing architecture and dimensional modeling
Experience designing and supporting large scale, production data pipelines
Strong scripting experience (Python, shell)
Experience with data virtualization tools (e.g., Denodo, Composite, dremio, Starburst)
Experience with DataOps practices, CI/CD, and observability
ETL Development and Process Support, may require weekend/off business hours work, * Bachelor’s degree or higher required
Discipline: Computer Science, Information Systems, Mathematics

Benefits & conditions

We offer a generous array of benefits, depending on the length of assignment. We also offer a referral bonus of up to $1,000. Ask us for more details!