Big Data Lead
Fa Etqo Saasfaprod1 Open · verified Oct 24, 2026 United States Senior Data Engineering
At a glance
Senior Data Engineering role at Fa Etqo Saasfaprod1. United States · no salary stated · we estimate $142,500–$193,650 across the United States.
Estimated pay
Fa Etqo Saasfaprod1 has not published a salary for this role. The figure below is our estimate, not theirs.
$142,500 – $193,650
What the middle half of senior data engineering roles in the United States paid, among postings that did state a salary.
Worked out from 470 postings that stated pay, median $162,500. Last updated Oct 24, 2026.
RoleData Engineering
SenioritySenior
LocationUnited States
PostedJul 6, 2026 · 3mo ago
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Build and refine ETL/ELT pipelines that ingest and transform large volumes of structured and unstructured data
- Use Python and PySpark for distributed processing, and inspect existing code for improvements
- Add validation, cleansing and reconciliation steps to protect accuracy and consistency across the data lifecycle
- Translate data needs from IT and business stakeholders into technical solutions
- Track job performance, investigate complex data issues and tune systems for scale
What you bring
- You can code confidently in Python, PySpark and SQL, with Microsoft SQL Server preferred
- You have worked with Hadoop or Spark and at least one cloud platform such as AWS or Azure
- You have used code versioning tools and set up CI/CD pipelines
- You understand database design, data models, schemas and data warehousing
Who this fits
This senior role suits someone who can resolve complex data issues independently. You’ll also contribute to code reviews, coding standards and automated testing and deployment.
From the employer
Responsibilities: • Development and Maintain Data Pipelines: Design, implement, and optimize end-to-end ETL/ELT pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. • Utilize Python and Pyspark: Write efficient, scalable and maintainable code in Python and leverage Pyspark for large-scale data processing in distributed computing environments. Also be able to review existing code and identify areas of improvement. • Ensure Data Quality and Integrity: Implement data validation, cleansing, transformation and reconciliation processes to ensure data accuracy and consistency throughout the data lifecycle. • Collaborate with Stakeholders: Work closely with IT teams and business stakeholders to gather data requirements and translate them to technical solutions. • Troubleshoot and Optimize: Monitor job performance, troubleshoot complex data issues and fine-tune for performance and scalability. • Adhere to Best Practices: Participate in code reviews, establish coding standards, and implement CI/CD pipelines for automated testing and deployment. Skills: • Strong hands-on coding proficiency in Python, Pyspark and SQL (Microsoft SQL Server preferred) • Experience with big data frameworks (Hadoop, Spark). • Experience with cloud platforms ( AWS, Azure or GCP) • Experience with Code versioning tools ( Bitbucket, Github ) • Experience with CI/CD and setting up pipelines. • Solid understanding of database design principles, data modelling, schemas and data warehousing solutions. • Excellent problem-solving and analytical skills to troubleshoot complex data issues independently.
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