AI Summary
Lead the modernization of a legacy data warehouse into a governed Databricks Lakehouse platform. Design and implement scalable batch and streaming pipelines using PySpark, Delta Lake, and medallion architecture. Ensure data quality, governance, and performance while collaborating with cross-functional teams.
Key Highlights
Modernize a 15-year-old data warehouse into a governed Databricks Lakehouse
Build and optimize batch/streaming pipelines with PySpark, Delta Lake, and medallion architecture
Implement data governance, quality, and lineage using Unity Catalog and automated validation
Key Responsibilities
Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows
Model and maintain a medallion (bronze/silver/gold) architecture for analytics, reporting, and machine learning consumers
Migrate legacy ETL and data warehouse workloads to the Lakehouse with validated data parity and minimal business disruption
Use AI tools like Claude or GitHub Copilot to accelerate development, including code scaffolding, testing, and documentation
Write clean, well-tested Python and SQL code; maintain high standards through code review and documentation
Optimize Spark jobs and Delta tables for performance and cost, including partitioning, clustering, caching, and cluster sizing
Implement data quality, lineage, and governance controls using Unity Catalog and automated validation checks
Debug, troubleshoot, and resolve pipeline failures, data defects, and production incidents
Participate in Agile or product-centric delivery practices including sprint planning and retrospectives
Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices
Technical Skills Required
Benefits & Perks
100% remote work
Competitive compensation with regular reviews
Annual learning budget for skill development
Nice to Have
Infrastructure as Code (IaC) using Terraform
CI/CD using Azure DevOps
Relational databases (PostgreSQL)
Logging and monitoring tools (Dynatrace, CloudWatch, Databricks system tables)
Agile or team-based development environments
Job Description
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
About The Role
We are looking for an experienced Senior Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers. This role also uses AI tools like Claude and GitHub Copilot to speed up development.
What You Will Do
- Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
- Model and maintain a medallion (bronze/silver/gold) architecture serving analytics, reporting, and machine learning consumers.
- Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal business disruption.
- Use Claude or Github Copilot as a development accelerator, generating code scaffolding, writing and reviewing tests, creating documentation and prototyping solutions.
- Write clean, well-tested Python and SQL; maintain high standards through code review and documentation.
- Optimize Spark jobs and Delta tables for performance and cost, including partitioning, clustering, caching, and cluster sizing.
- Implement data quality, lineage, and governance controls using Unity Catalog and automated validation checks.
- Debug, troubleshoot, and resolve pipeline failures, data defects, and production incidents.
- Participate in Agile or product-centric delivery practices including sprint planning and retrospectives.
- Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices.
Interested in remote work opportunities in Data Science? Discover Data Science Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- 4+ years of professional experience in data engineering, featuring direct expertise with Apache Spark and cloud-based data architectures.
- Strong hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake.
- Advanced SQL and Python, with strong data modeling skills across dimensional and Lakehouse patterns.
- Experience with streaming ingestion using Structured Streaming, Auto Loader, Kafka, or Event Hubs.
- Experience with workflow orchestration (Databricks Workflows, Airflow, or Azure Data Factory).
- Experience with legacy platform migrations, ETL modernization, or managing data hygiene when porting old systems.
- Strong problem-solving, collaboration, and communication skills, including mentoring junior engineers and explaining data concepts to non-technical stakeholders.
- Familiarity with Unity Catalog, data governance, access control, and PII handling.
- Experience with dbt or an equivalent transformation framework.
- Familiarity with secure coding standards and industry security best practices.
- Experience delivering production data platforms at scale.
- Upper-intermediate English level.
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Experience with Infrastructure as Code (IaC) using Terraform and CI/CD using Azure Devops.
- Experience working with relational databases (specifically PostgreSQL) and data persistence concepts.
- Familiarity with logging and monitoring tools (e.g., Dynatrace, CloudWatch, Databricks system tables).
- Experience working in Agile or team-based development environments preferred.
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
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