Sr. Data Engineer (Hybrid)

TM Floyd & Company (TMF); Richmond (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

TM Floyd & Company in Richmond, VA seeks a highly experienced Senior Data Engineer to support a large-scale enterprise data environment. You will build robust ETL/ELT pipelines, develop scalable batch and streaming solutions, and optimize high-volume data processing using SQL-centric approaches.

The ideal candidate has 5-7+ years of data engineering, strong SQL and ELT skills, and hands-on experience with Oracle Exadata, Snowflake, Talend, dbt, or Informatica, plus DataOps and observability

Qualifications

• 5-7+ years of Data Engineering experience.
• Advanced SQL and ELT expertise.
• Experience with Oracle Exadata, Snowflake, or similar data warehouses.
• Hands-on with ETL/ELT platforms such as Talend, dbt, or Informatica.
• Knowledge of dimensional modeling and data governance.

Responsibilities

• Build and support enterprise-scale ETL/ELT data pipelines.
• Develop scalable batch and incremental processing solutions.
• Design and optimize high-volume SQL-centric data pipelines.
• Implement reliable error handling, restartability, monitoring, and alerting.
• Develop streaming pipelines using Kafka, Kinesis, Spark Streaming, or similar.
• Perform data cleansing, validation, reconciliation, and enrichment.
• Optimize warehouse performance via indexing, partitioning, and query tuning.
• Support data quality investigations and root-cause analysis.
• Implement DataOps, CI/CD, observability, governance, lineage, and auditability.
• Partner with architects, infrastructure, application, and governance teams.
• Translate complex requirements into practical solutions.
• Participate in design and code reviews.
• Troubleshoot production issues to improve reliability and cost.

Skills

SQL/ELT

Oracle Exadata

Snowflake

ETL/ELT tools

Dimensional modeling

Python scripting

DataOps/CI/CD

Data quality

5-7+ yrs exp

Kafka/Spark

Tools

Talend

dbt

Informatica

Job description

TM Floyd & Company is seeking a highly experienced Senior Data Engineer to support a large-scale enterprise data environment in Richmond, VA.

• U.S. Citizens Only
• Important Eligibility Requirement: Due to the sensitive nature of this position and export control restrictions, candidates must be U.S. Citizens. Please do not apply unless you meet this requirement.
• MUST be located in or near Richmond, VA

What You'll Do

• Build and support enterprise-scale ETL/ELT data pipelines
• Develop scalable batch and incremental processing solutions
• Design and optimize high-volume SQL-centric data pipelines
• Implement reliable error handling, restartability, monitoring, and alerting
• Develop streaming pipelines using Kafka, Kinesis, Spark Streaming, or similar technologies
• Perform data cleansing, validation, reconciliation, and enrichment
• Optimize warehouse performance using indexing, partitioning, and query tuning
• Support data quality investigations and root-cause analysis
• Implement DataOps, CI/CD, observability, governance, lineage, and auditability
• Partner with architects, infrastructure teams, application teams, and governance teams
• Translate complex or ambiguous requirements into practical technical solutions
• Participate in design and code reviews
• Troubleshoot production issues and improve reliability, performance, and cost

Required Technical Skills

• Advanced SQL / ELT / performance tuning
• Oracle Exadata, Snowflake, or similar data warehouse
• Talend, dbt, Informatica, or comparable ETL/ELT platforms
• Data warehousing and dimensional modeling
• Python and shell scripting
• DataOps / CI/CD / observability
• Batch and incremental processing
• Data quality, lineage, governance, and auditability
• 5-7+ years of Data Engineering experience

Nice to Have

• AI/ML or advanced analytics pipelines
• Cloud data warehouse cost/performance optimization
• Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink

Ideal Candidate

The ideal candidate is a hands-on Senior Data Engineer with 5-7+ years of experience designing, developing, optimizing, and supporting large-scale production data pipelines. This person should have advanced SQL and ELT expertise, strong experience with Oracle Exadata, Snowflake, or similar data warehouses, and hands-on experience with enterprise ETL/ELT platforms such as Talend, dbt, or Informatica. They should understand dimensional modeling, incremental processing, data quality, restartability, observability, auditability, and data lineage, while also being comfortable with Python/shell scripting and streaming technologies such as Kafka, Kinesis, or Spark Streaming. Experience with data virtualization tools such as Denodo, Dremio, Starburst, or Composite is highly valuable. Candidates who have worked in large-scale commercial utilities environments or major capital-project organizations are especially encouraged to apply.