Senior Data Science Analyst

Position: Senior Data Science Analyst

Location: Richmond, Virginia

Duration: W2 Contract

Job : 176936

The Senior Data Science Analyst will play a critical role in designing, building, and optimizing scalable, reliable data pipelines at an enterprise level. This position requires hands‑on expertise in data engineering, a deep understanding of data warehousing architecture, and the ability to implement advanced ELT solutions. The role also involves troubleshooting complex data challenges, ensuring best practices, and collaborating with architecture and platform teams to enhance the overall data ecosystem.

• Design and build end‑to‑end data pipelines and ETL/ELT solutions to support analytics, reporting, and AI/ML use cases.
• Develop, test, and deploy scalable patterns for batch and incremental data processing.
• Optimize data modeling, transformation logic, and performance strategies.
• Evaluate and integrate tools, frameworks, and platform capabilities to meet project requirements.
• Implement enterprise‑grade error handling, restartability, and monitoring for data pipelines.
• Design and maintain scalable, low‑latency streaming data pipelines using technologies like Kafka, Kinesis, or Spark Streaming.
• Ensure data pipelines meet security, access control, and governance requirements.
• Collaborate with governance and Data Ops teams on metadata, lineage, and auditability.
• Proactively identify opportunities for reliability, performance, and cost optimization.
• Support production troubleshooting and root cause analysis.
• Participate in design and code reviews to enforce quality and best practices.
• Translate ambiguous requirements into well‑designed technical solutions.

• 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.
• Strong scripting experience (Python, shell).
• Experience with data virtualization tools (e.g., Denodo, Composite, Dremio, Starburst).
• Experience with Data Ops practices, CI/CD, and observability.
• Ability to work independently and deliver results under pressure.
• Bachelor’s degree or higher in Computer Science, Information Systems, or Mathematics.

• Experience supporting AI/ML or advanced analytics pipelines.
• Cloud platform experience (AWS, Azure, or Google Cloud Platform).
• Prior experience influencing enterprise data standards or reference architecture.
• Experience optimizing cost and performance in cloud data warehouses.
• Hands‑on experience with Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink.

$55 – $61

The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full‑time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work.