Lead Data Engineer (Hands-On) — PySpark, Hive & Oracle

Acunor Inc.; Jersey City (NJ); Vor Ort; USD 140.000 - 180.000; Vollzeit

Zusammenfassung

Acunor Inc. is seeking a hands-on Lead Data Engineer to design and deliver enterprise-scale data pipelines and feature stores supporting analytics and AI use cases.

You will lead the architecture and development of batch processing solutions using PySpark, Impala SQL, Hive and Oracle, while owning data quality, reconciliation, and performance tuning. Mentoring engineers and collaborating with stakeholders are essential responsibilities.

Qualifikationen

• 8+ years of Data Engineering / Data Platform experience.
• 5+ years hands-on PySpark and ETL/ELT development.
• Advanced SQL and pipeline performance tuning.
• Strong data architecture / database architecture experience.
• Hands-on Hive and Oracle experience.
• Technical leadership on complex data engineering programs.
• Linux, Git/Bitbucket, and CI/CD.
• Experience with CA7 or equivalent batch scheduling.

Aufgaben

• Lead the architecture and development of enterprise-scale data pipelines.
• Build scalable PySpark and Impala SQL solutions.
• Develop ETL/ELT pipelines using Hive and Oracle.
• Own data architecture, feature logic, data quality, and reconciliation.
• Perform pipeline performance tuning, monitoring, and failure recovery.
• Manage batch scheduling and dependencies using CA7 or equivalent.
• Conduct design/code reviews and hands-on troubleshooting.
• Establish Git/Bitbucket, CI/CD, and testing practices.
• Lead production releases and SDLC/change-management activities.
• Work with business, analytics, and technology stakeholders.
• Mentor engineers while remaining hands-on technically.

Kenntnisse

8+ years data eng

5+ years PySpark

SQL proficiency

Data architecture

Hive & Oracle experience

Linux & Git/Bitbucket

CI/CD

Batch scheduling (CA7)

Mentoring

Troubleshooting

Tools

PySpark

Impala SQL

Hive

Oracle

Linux

Git/Bitbucket

CA7

Jobbeschreibung

Acunor Inc. is seeking a hands-on Lead Data Engineer to design and deliver enterprise-scale data pipelines and feature stores supporting analytics and AI use cases.

You will lead the architecture and development of batch processing solutions using PySpark, Impala SQL, Hive and Oracle, while owning data quality, reconciliation, and performance tuning. Mentoring engineers and collaborating with stakeholders are essential responsibilities.