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Lead Data Engineer

Acunor InfotechJersey City, NJ🇺🇸United StatesPosted Oct 8, 2026

Why This Role Stands Out

This hybrid Lead Data Engineer role offers a fantastic opportunity to drive enterprise data modernization initiatives using cutting-edge technologies like PySpark, Snowflake, and AWS. You'll thrive here if you're a seasoned data professional eager to lead technical design, mentor a team, and build scalable cloud data solutions within the dynamic insurance and financial services sector. Don't miss the chance to make a significant impact and grow your career in this exciting position.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Jersey City, NJ, United States
Posted
21 hours ago
OracleSQLETLScrumAgileGitHiveJira

Job Description

Location: NY / NJ / Pittsburgh Onsite

Employment Type: Full-Time

Experience: 8+ Years

Job Summary

We are looking for a hands-on Technology Engineering Lead to design and deliver enterprise-scale data engineering solutions, including a batch feature store supporting analytics and AI use cases.

This is a technical leadership + individual contributor role. The ideal candidate must be comfortable working directly with clients while remaining deeply hands-on with PySpark, SQL, database architecture, and ETL/ELT pipeline development.

Key Responsibilities

  • Lead architecture and development of enterprise-scale data pipelines.

  • Design and build scalable PySpark and Impala SQL solutions.

  • Develop ETL/ELT pipelines across Hive and Oracle data platforms.

  • Own data architecture, feature logic, data quality, and reconciliation.

  • Drive pipeline performance tuning, monitoring, and failure recovery.

  • Manage batch scheduling and dependencies using CA7 or equivalent.

  • Conduct design reviews, code reviews, and hands-on troubleshooting.

  • Establish Git/Bitbucket, CI/CD, and testing practices.

  • Lead production releases and SDLC/change-management activities.

  • Work directly with business, analytics, and technology stakeholders.

  • Mentor engineers while remaining actively involved in technical delivery.

Required Qualifications

  • 8+ years of Data Engineering / Data Platform experience.

  • 5+ years of hands-on PySpark and enterprise ETL/ELT development.

  • Advanced SQL and strong pipeline performance-tuning skills.

  • Strong database/data-platform architecture experience.

  • Hands-on experience with Hive and Oracle.

  • Technical leadership experience across complex data-engineering programs.

  • Experience with Linux, Git/Bitbucket, and CI/CD.

  • Strong client-facing communication skills.

  • Ability to work effectively in a fast-paced environment.

Preferred Skills

  • Banking / Financial Services experience.

  • CA7 or equivalent batch scheduling tools.

  • Jira and Agile/Scrum experience.

  • Experience with AI-assisted development tools.

Primary Skills

PySpark, SQL, ETL/ELT, Data Engineering, Data Architecture, Hive, Oracle, Impala SQL, Database Architecture, Data Pipelines, Performance Tuning, CI/CD, Git/Bitbucket, Linux, CA7

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