Senior Data Engineer (Databricks & PySpark)

Optiveum; United States; Remote; USD 53,000 - 89,000; Full time

Job summary

Optiveum is seeking a Senior Data Engineer to design and operate the Sustainability Data Foundation built on Databricks, Delta Lake, and PySpark. You will develop scalable data products and pipelines supporting regulatory reporting and advanced analytics.

The role emphasizes data quality, governance, CI/CD, IaC, and close collaboration with sustainability experts and analysts. Fluent English and proactive problem-solving are essential.

Qualifications

• 5–7 years of experience designing, developing, and operating data platforms and pipelines.
• Extensive hands-on experience with Databricks (including Azure Databricks and Databricks Workflows) in production environments.
• Expert-level proficiency in PySpark, Python, Spark SQL, Data Modelling, and Data Pipeline Design.
• Experience implementing CI/CD pipelines for data engineering workloads, Git-based development, and version control.
• Solid understanding of data lineage, metadata management, governance, auditing, and validation frameworks.
• Fluent English (both written and spoken).
• Proactive, self-driven mindset with strong troubleshooting and root-cause analysis skills.

Responsibilities

• Data Engineering & Product Development: Design and implement scalable data products using Databricks, Delta Lake, and PySpark.
• Build and maintain data pipelines processing complex datasets from ERP, procurement, sustainability, and external systems.
• Performance Optimization: Optimize workloads for performance, scalability, and cost efficiency, building reusable engineering patterns.
• Data Quality & Governance: Implement automated data quality controls throughout the data lifecycle.
• Platform Engineering & DevOps: Implement CI/CD pipelines, automated deployments, testing frameworks, and IaC.
• Stakeholder Collaboration: Partner with sustainability experts, business analysts, and reporting teams to support requirements gathering and production releases.

Skills

Databricks

PySpark

Python

Spark SQL

Data Modeling

Data Pipeline Design

CI/CD

Git

Data Governance

Data Lineage

Metadata Management

English

Tools

Azure Databricks

Databricks Workflows

Delta Lake

Infrastructure as Code

Job description

Senior Data Engineer (Databricks & PySpark)

Location: 100% Remote (Warsaw, PL)

Rate: Up to 38 EUR / hour

Mode of work: Full-time (40 hours/week)

Contracting party: Optiveum (B2B Cooperation Agreement)

About the role:

We are seeking an experienced Senior Data Engineer on behalf of our client to design, build, and operate their Sustainability Data Foundation (SDF). The SDF supports trusted, scalable, and auditable sustainability reporting and analytics through a modern data platform built on Databricks.

You will join a Sustainability Data & AI team that values reliability, operational excellence, and practical solutions over unnecessary complexity. The focus of this role is to deliver data products and pipelines that enable regulatory compliance and advanced analytics.

Key Responsibilities:

• Data Engineering & Product Development: Design and implement scalable data products using Databricks, Delta Lake, and PySpark. Build and maintain data pipelines processing complex datasets from ERP, procurement, sustainability, and external systems.

• Performance Optimization: Optimize workloads for performance, scalability, and cost efficiency, building reusable engineering patterns.

• Data Quality & Governance: Implement automated data quality controls throughout the data lifecycle. Proactively identify and resolve data issues before they impact reporting.

• Platform Engineering & DevOps: Implement CI/CD pipelines, automated deployments, testing frameworks, and Infrastructure as Code (IaC). Support platform security controls and access management.

• Stakeholder Collaboration: Partner with sustainability experts, business analysts, and reporting teams to support requirements gathering, solution design, and production releases.

Required Qualifications:

• 5–7 years of experience designing, developing, and operating data platforms and pipelines.

• Extensive hands-on experience with Databricks (including Azure Databricks and Databricks Workflows) in production environments.

• Expert-level proficiency in PySpark, Python, Spark SQL, Data Modelling, and Data Pipeline Design.

• Experience implementing CI/CD pipelines for data engineering workloads, Git-based development, and version control.

• Solid understanding of data lineage, metadata management, governance, auditing, and validation frameworks.

• Fluent English (both written and spoken).

• Proactive, self-driven mindset with strong troubleshooting and root-cause analysis skills.

Nice to have:

• Experience with sustainability reporting, ESG data, and regulatory reporting requirements.

• Knowledge of procurement, supplier, finance, and ERP data domains.

• Experience developing Databricks applications, dashboards, or user-facing data tools.

Please note: Optiveum acts as the recruitment partner and the direct contracting party for this position. The selected candidate will sign a cooperation agreement directly with Optiveum.