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.

Lead Data Engineer with AWS

Key Responsibilities

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

Required Skills & Qualifications

Technical Skills

• Deep experience with Snowflake including data modeling, performance tuning

• Proficiency with AWS services — S3, Glue, Lambda, EMR, Redshift, Step Functions, CloudWatch

• Strong experience building distributed data processing frameworks with Apache Spark / PySpark

• 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

Experience Requirements

• 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

Education

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

------------------------------------------------------------------------------------------------------------------------

Lead Data Engineer with Azure

Key Responsibilities:

• 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 DevOps teams in a cloud-native environment.

Must-Have Skills:

• 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.

Good-to-Have Skills:

• Experience with DataStage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions.

• Familiarity with Python or PySpark for custom data transformations.

• Understanding of CI/CD pipelines and DevOps for data workflows.

• Exposure to data governance, metadata management, or data catalog tools.

• Knowledge of business intelligence tools (e.g., Power BI, Tableau) is a plus.

Qualifications:

• 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.