Senior Data Engineer

Position Summary The Senior Data Engineer will design, build, and optimize large‑scale data solutions to support analytics, reporting, and investment decision‑making within Investment Management. This role requires deep expertise in modern data engineering, distributed data processing, and cloud‑native development. The engineer will work extensively with Databricks, PySpark, SQL, Snowflake, and Python, while leveraging Azure services and GenAI tools such as CortexAI and GitHubCopilot to accelerate development and automation. Key Responsibilities Design, develop, and optimize large‑scale data pipelines and ETL workflows within the Databricks platform. Develop and maintain complex data models and transformation logic using PySpark, Python, and SQL. Build reusable, modular data engineering components and enforce best practices for performance, reliability, and cost efficiency. Apply GenAI tools (GitHubCopilot, Snowflake CortexAI) to improve development velocity and code quality. Ensure strong data governance, lineage, observability, and security across all pipelines and platforms. Collaborate with cross‑functional teams to translate business requirements into scalable technical solutions. Provide technical expertise and mentor junior engineers in data engineering best practices. Participate in Agile ceremonies and drive continuous improvement across the engineering lifecycle. Requirements & Qualifications 5–7years of hands‑on experience in data engineering with strong coding skills. Proven experience with Databricks, including PySpark development, notebooks, Delta Lake & Lakehouse architecture, jobs/workflows/cluster management. Strong proficiency in Python and SQL for building scalable, distributed data pipelines and Snowflake as a data warehouse. Strong understanding of data lake architectures, medallion patterns, and cloud‑native data engineering. Familiarity with GenAI tools (e.g., GitHubCopilot, CortexAI) to accelerate development. Experience designing and integrating API‑driven data ingestion. Advanced understanding of dimensional modeling, data warehousing, and distributed systems. Excellent problem‑solving skills and ability to operate in a fast‑paced environment. Strong communication and stakeholder management skills. Nice to have: Experience with LLMs, NLP, or GenAI‑driven data workflows; Experience with DBT; Experience with data quality and observability frameworks such as SODA, Great Expectations, or DBT tests. Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field. Certifications in Azure Data Engineering, Databricks, or Snowflake are a plus. Experience in Investment Management or Financial Services preferred. Compensation Annual base salary range: $125,980 – $157,470USD (location dependent). Annual cash incentives and other long‑term incentive options may apply. Benefits Health, dental, vision, and life insurance plans 401(k) Savings plan with up to 6% company matching Employer paid cash balance retirement plan (4%) Tuition reimbursement up to $5,250/yr Paid time off: 20days, nine paid holidays, and a flexible Diversity Celebration Day Paid volunteer time: 40hrs per calendar year Equal Employment Opportunity Voya Financial is an equal‑opportunity employer. Voya Financial provides equal opportunity to qualified individuals regardless of race, color, sex, national origin, citizenship status, religion, age, disability, veteran status, creed, marital status, sexual orientation, gender identity, genetic information, or any other status protected by state or local law. Reasonable accommodations are available for qualified individuals with disabilities. #J-18808-Ljbffr