Database Engineer

Innova Solutions•New York, NY

1d•Remote

About The Position

A client of Innova Solutions is immediately hiring for a Database Engineer. This is a Full-time Contract (W2) role for a Database Engineer with a duration of 4+ months. The role is remote and requires a strong background in Python, Spark/PySpark, RESTful APIs, API versioning, input validation, pagination, and error standards using Python frameworks like FastAPI, Django, or Flask, as well as experience with orchestration tools such as Airflow or Dagster.

Requirements

5+ years of experience in Data Engineering or equivalent combination of education, training, and hands-on experience
5+ years of strong hands-on programming experience in Python, with the ability to build production-grade data pipelines, reusable frameworks, and data processing components
4+ years of hands on experience in Spark / PySpark, building and optimizing spark pipelines.
2+ years of hands on experience building backend systems, implementing RESTful APIs, API versioning, input validation, pagination, and error standards in Python using FastAPI / Django / Flask
Exposure to data orchestration and pipeline tools (e.g., Airflow, Dagster, or similar)

Nice To Haves

Python, Spark / PySpark, RESTful APIs, API versioning, input validation, pagination, and error standards in Python using FastAPI / Django / Flask, Airflow, Dagster, or similar

Responsibilities

Architect and scale data platforms, designing and evolving enterprise data platforms, pipelines, and storage systems (warehouses/lakehouses), applying strong data modeling techniques to support scalable analytics across diverse data sources.
Build robust data pipelines and ingestion frameworks, developing reusable ETL/ELT frameworks and connectors to ingest and process structured and unstructured data using distributed processing systems (e.g., Spark/PySpark) for batch and streaming workloads.
Develop production-grade data services, implementing reliable backend systems and RESTful APIs in Python, ensuring best practices in code quality, performance optimization, testing, and maintainability.
Ensure data reliability, governance, and operational excellence by managing pipeline orchestration, monitoring, and lifecycle using tools like Airflow, while enforcing data quality, lineage, security, and compliance standards.
Drive end-to-end data engineering projects, solve complex problems, collaborate with cross-functional teams, and provide technical leadership and mentorship to engineers.