Sr Data Engineer, Specialist

We are looking for a Sr Data Engineer with in-depth expertise in AWS, Databricks, and modern data
architecture and data modeling to help build the next generation of our data foundation , including data
platforms such as Advisor360, CRM integrations, ETF/MF data pipelines, and other enterprise analytics assets.

This is a senior, highly autonomous role. You will operate as a technical consultant and data architecture
thinker, working closely with stakeholders to understand ambiguous business needs, conduct independent
investigations, and design solutions that are scalable, reliable, and aligned to both business and technology
goals.

Ideal candidates have 5+ years of data engineering experience and thrive in environments where they drive
clarity, define standards, and elevate engineering best practices across the team

Responsibilities:Data Engineering & Architecture:

• Design, build, and optimize scalable, secure, and repeatable data pipelines using AWS (S3, Glue, Lambda, Step Functions, Redshift, IAM) and Databricks (PySpark, Lakeflow, Delta Lake, Unity Catalog).

• Serve as the technical leader for data ingestion pipelines, modeling new datasets such as Advisor360, CRM, ETF, and Mutual Fund platforms.

• Apply strong data modeling (dimensional, canonical, and domain-driven) principles to support analytics, reporting, and AI/ML use cases.

• Ensure alignment with enterprise data architecture standards, promoting reusability, governance, and long-term maintainability.

Consultative Problem Solving:

• With limited guidance, independently perform deep investigations, identify data issues, and propose solutions that balance performance, cost, risk, and business needs.

• Engage business stakeholders to gather ambiguous requirements, ask the right questions, and translate them into clear technical designs.

• Provide thought leadership and recommend technical patterns, frameworks, and toolsets.

Data Quality, Reliability & Operations:

• Implement robust data quality frameworks, monitoring, and alerting to ensure high trust in business-critical data assets.

• Troubleshoot data inconsistencies and ensure proper logging, testing, and recovery mechanisms across pipelines.

• Lead regression testing, software upgrades, and production deployments with strong change control discipline.

Collaboration & Leadership:

• Lead all phases of solution development—from design to deployment and operationalization.

• Mentor and guide other engineers in coding standards, architecture patterns, Databricks best practices, and AWS platform usage.