Senior Data Engineer

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 (GitHub Copilot, Snowflake Cortex AI) 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
• 5-7 years 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., GitHub Copilot, Cortex AI) 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.

Requirements

• 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.
• Education & Certifications
• 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.
• #LI-LW1
• Compensation Pay Disclosure:
• Voya is committed to pay that's fair and equitable, which means comparable pay for comparable roles and responsibilities.
• Actual compensation offered may vary from the posted salary range based upon the candid

Benefits

Additional Information

Together we fight for everyone's opportunity for a better financial future. We will do this together - with customers, partners and colleagues. We will fight for others, not against: We will stand up for and champion everyone's access to opportunities. The status quo is not good enough ... we believe every individual and every community deserves access to financial opportunities. We are determined to support both individuals and communities in reaching a better financial future. We know that reaching this future depends on our actions today. Like our Purpose Statement, Voya believes in being bold and committed to action. We are committed to a work environment where the differences that we are born with - and those we acquire throughout our lives - are understood, valued and intentionally pursued. We believe that our employees own our culture and have a responsibility to foster an environment where we all feel comfortable bringing our whole selves to work. Purposefully bringing our differences together to positively influence our culture, serve our clients and enrich our communities is essential to our vision. Are you ready to join a company with a strong purpose and a winning culture? Start your Voyage - Apply Now 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 Cortex AI and GitHub Copilot to accelerate development and automation. This position is ideal for a highly experienced engineer with strong technical expertise , who can drive best practices and deliver scalable, high ‑ quality data products.

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