Lead Data Engineering

Job Title: Lead Data Engineering
Job Location: USA (Ohio
Job Type: Contract

Job Description:

• Data Lake Architecture & Governance: Design and implement a scalable, governed data lake solution tailored for analytical scaling.

• Pipeline Development: Build, orchestrate, and optimize high-performance data processing pipelines using Python, Polars, DuckDB, and SQL.

• Containerization & Deployment: Implement and manage Docker/containers for running data jobs reliably using Azure Containers.

• Security & Access Management: Drive secure development practices. Create and manage Azure roles and permissions (RBAC) to ensure strict data governance and secure environments.

• Cross-Functional Collaboration: Partner closely with the BI team to understand their reporting requirements (Power BI) and deliver the data models they need.

• CI/CD Implementation: Establish and maintain automated deployment pipelines using Azure DevOps.

Required Skills & Qualifications

• Data Engineering Expertise: Proven track record in core Data Engineering principles, data modeling, and data warehouse/data lake architecture.

• Core Programming: Exceptional proficiency in Python, SQL, Polars, and DuckDB.

• Cloud Infrastructure: Deep familiarity with the Azure Environment, including deploying and managing Azure Containers.

• DevOps & Automation: Strong practical knowledge of CI/CD pipelines (Azure DevOps) and Docker/containerization.

• Security Acumen: Solid understanding of cloud security, specifically in configuring Azure roles, identities, and access management.

• Domain Knowledge: Previous experience working with Fintech industry data, understanding its unique security and analytical requirements.

• Communication: Excellent communication skills with the ability to translate technical concepts to BI teams and business stakeholders.

• Team Leadership: Should have experience managing a team of 4-5 Data Engineers

• Collaboration: Strong capabilities of collaborating with Senior Stakeholder, Product Owner and team

• Consultative Mindset: Capabilities to provide an optimized solution and have FinTech and Wealth Management domain understanding

• Overall Experience: Overall, 8-10 Years of experience with minimum of 5-6 years of experience working on Data lake solutions

Preferred Qualifications

• Familiarity with Microsoft Dynamics, Salesforce, or similar CRM platforms.

• Knowledge of Azure Data Factory (ADF) for data integration.

• Experience with Microsoft Purview for unified data governance.

Technology Experience

• Processing: Python, Polars, DuckDB, SQL

• Cloud & Infrastructure: Azure Environment, Azure Containers (Docker)

• CI/CD: Azure DevOps

• BI & Analytics: Power BI

• Source Systems: Microsoft Dynamics, Salesforce