Data Engineer: Build Scalable Pipelines & Data Lakes

Yankalatam; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

SportsEngine is seeking a Data Engineer to design, build, and maintain scalable data systems powering analytics and operations. You will develop data pipelines, implement ETL/ELT processes, ingest data from internal systems, APIs, third-party providers, and real-time streams, and shape data models for data lakes and warehouses.

You will collaborate with product and engineering teams to translate business needs into robust data solutions, ensure data quality, and participate in Agile ceremonies

Qualifications

• Strong experience designing and building data pipelines.
• Expertise in ETL/ELT processes and data ingestion.
• Experience with data lake architectures and modern data platforms.

Responsibilities

• Design, build, and maintain scalable data pipelines and data processing systems.
• Develop and optimize ETL/ELT processes for batch and real-time data ingestion.
• Ingest and process data from internal systems, APIs, third-party platforms, and streaming sources.
• Design and maintain data models, data lakes, and data warehouse structures.
• Write clean, efficient, and reusable code for large-scale data processing.
• Collaborate with product managers, data teams, and engineering teams to translate business needs into data solutions.
• Ensure data quality, integrity, and availability across systems.
• Monitor, troubleshoot, and resolve production issues related to data pipelines and workflows.
• Contribute to improving code quality, system reliability, and best engineering practices.
• Actively participate in Agile ceremonies (standups, sprint planning, retrospectives)

Skills

Python

SQL

PySpark

Airflow

AWS ecosystem

ETL/ELT pipelines

Data lakes

API integration

CI/CD / TDD (basic)

Tools

Terraform

Talend

Job description

SportsEngine is seeking a Data Engineer to design, build, and maintain scalable data systems powering analytics and operations. You will develop data pipelines, implement ETL/ELT processes, ingest data from internal systems, APIs, third-party providers, and real-time streams, and shape data models for data lakes and warehouses.

You will collaborate with product and engineering teams to translate business needs into robust data solutions, ensure data quality, and participate in Agile ceremonies