Data Engineer

One of our Client is seeking Lead Data Engineers in NJ and Ohio Respectively. Due to the requirement, only visa independent candidates - GC / USC/ H4 EAD need to apply for this role who can comfortably work on W2 tax-term.

Below are the details for each:

Lead Data Engineer with AWS
- No. of openings 1 - location:
Jersey City, NJ

Lead Data Engineer with Azure
- No. of openings 1 - location:
Remote and Ohio

Candidate should be having a minimum of 3-4 years of Lead experience handling a team of engineers and providing technical leadership and mentorship to junior Data Engineers.

• Technical Delivery
  • Design and implement end-to-end data pipelines using PySpark, Snowflake, and AWS cloud services
  • Architect scalable ELT/ETL workflows and data warehouse models supporting insurance analytics use cases
  • Drive data migration and modernization efforts from legacy environments to cloud-native platforms
  • Develop and review complex SQL transformations, stored procedures, and data quality validation frameworks
  • Establish and enforce data engineering standards, coding best practices, and pipeline documentation
  • Provide hands‑on troubleshooting and performance optimization across the data stack
• Team Coordination & Stakeholder Engagement
  • Coordinate day‑to‑day activities across onshore and offshore data engineering teams to ensure timely delivery
  • Serve as a technical point of contact for business stakeholders, translating requirements into engineering deliverables
  • Facilitate requirement‑gathering sessions, sprint planning, and status updates with project teams
  • Communicate project progress, risks, and dependencies to project managers and client stakeholders
  • Mentor junior engineers and conduct code reviews to uphold quality standards
  • Collaborate with data architects, analysts, and QA teams throughout the project lifecycle

• Deep experience with Snowflake including data modeling, performance tuning
• Proficiency with AWS services — S3, Glue, Lambda, EMR, Redshift, Step Functions, Cloud Watch
• Strong experience building distributed data processing frameworks with Apache Spark / Py Spark
• Advanced SQL skills — complex transformations, query optimization, and dimensional modeling
• Expertise in DWH design patterns — Kimball, Inmon, Data Vault, star and snowflake schemas
• Demonstrated experience leading or contributing to cloud migration and legacy modernization programs
• Familiarity with tools such as dbt, Apache Airflow, AWS Glue, or similar orchestration frameworks
• Solid Python programming for data engineering and automation tasks

• 6–9 years of progressive experience in data engineering
• Prior experience in insurance, financial services, or regulated industries preferred
• Experience coordinating distributed teams across time zones (onshore/offshore model)
• Demonstrated ability to engage with non-technical stakeholders and translate business requirements
• Exposure to Agile/Scrum delivery methodology

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field

• Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT
• Build and maintain data integration workflows from various data sources to Snowflake
• Write efficient and optimized SQL queries for data extraction and transformation
• Work with stakeholders to understand business requirements and translate them into technical solutions
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability
• Provide technical leadership and mentorship to junior data engineers
• Maintain and enforce data quality, governance, and documentation standards
• Collaborate with data analysts, architects, and Dev Ops teams in a cloud-native environment

• Strong experience with Azure Cloud Platform services
• Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines
• Proficiency in SQL for data analysis and transformation
• Hands‑on experience with Snowflake and SnowSQL for data warehousing
• Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse
• Experience working in cloud-based data environments with large-scale datasets

• Experience with Data Stage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions
• Familiarity with Python or PySpark for custom data transformations
• Understanding of CI/CD pipelines and Dev Ops for data workflows
• Exposure to data governance, metadata management, or data catalog tools
• Knowledge of business intelligence tools such as Power BI or Tableau is a plus

• Bachelor’s degree in Data Engineering or a related field
• 8+ years of experience in data engineering roles using Azure and Snowflake
• Strong problem-solving, communication, and collaboration skills