We're hiring a Data Engineer (SQL, ELT) to join our team in Richmond, VA. This role offers a hybrid schedule, with one week onsite and one week remote.
Skills & Qualifications:
- 5 to 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 with:
- Designing and supporting large-scale, production data pipelines
- Data virtualization tools (e.g., Denodo, Composite, Dremio, Starburst)
- Experience with DataOps practices, CI/CD, and observability
- Strong scripting experience (Python, Shell)
- ETL Development and Process Support, may require weekend/off business hours work
Key Responsibilities:
- 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
- Perform on-the-fly data cleaning, validation, and enrichment before data reaches its final destination
- Use strategies, such as Indexing and partitioning, to fine-tune the data warehouse and big data environments to improve query response time and scalability
Education/Certifications:- Bachelor's or higher in Computer Science, Information Systems, or Mathematics
Ideal Candidate:
The ideal candidate will have extensive experience in Data Engineering, with a strong background in SQL, ELT patterns, and data warehousing. They should be adept at building scalable data pipelines and have hands-on experience with ETL/ELT platforms and scripting languages, such as Python. Familiarity with data virtualization tools and DataOps practices is essential. A Bachelor's degree in Computer Science, Information Systems, or Mathematics is required.
The hourly rate for this position is $62.57.
TM Floyd & Company is an equal opportunity employer and values diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.
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!
TM Floyd & Company participates in E-VERIFY
AAP, EEO