Job Description AgileEngine is an Inc. **** 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 a Senior Data Engineer to build batch and streaming pipelines on Databricks using PySpark and Delta Lake.
This person migrates legacy data warehouse and ETL workloads onto a governed Lakehouse, modeling a medallion architecture that powers analytics and AI use cases.
Strong SQL, Python, and experience with Unity Catalog governance round out the role.
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.
- Collaborate with DevOps, platform,



and analytics engineers on observability, security, and compliance best practices.
MUST HAVES - 3+ 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.
- 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.
NICE TO HAVES - 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.
PERKS AND BENEFITS - Professional growth : Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- A selection of exciting projects : Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- Flextime : Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
Requirements -+3 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.
-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.

📌 Senior Databricks Engineer Id86295 (Xico)
🏢 Agileengine
📍 Xico