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 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.
- 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. MUST HAVES - 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. 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 - -+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.

Databricks

Engineer ID86297 • Pereira, RIS, co

📌 Databricks Engineer Id86297 (Risaralda)
🏢 Ingepsy
📍 Risaralda