Mid/Senior Data Engineer (Databricks)

Exerizon – Expect More

Exerizon is a fast-growing strategy and technology consulting firm founded by former senior leaders from global consulting and cloud organizations. We help leading companies deliver complex business and technology transformations, with a strong focus on financial services and other regulated industries.

We combine management consulting (corporate and digital strategy, operational excellence) with deep technology expertise (cloud strategy and migration, cloud security, application modernization, data & AI, Generative AI). Our projects span from board-level strategy to hands-on implementation.

What makes us different:

• Ownership mindset from day one – consultants participate in the firm’s success.
• High-impact work – direct exposure to senior executives and mission-critical programs.
• Results-driven culture – we take responsibility for outcomes, not just recommendations.
• Fast growth & ambition – we are building a next-generation consulting firm with global aspirations.

At Exerizon, you will work on meaningful transformations, grow alongside experienced leaders, and help shape a firm designed for exceptional performance.

• 2–4 years of experience (mid level) or 4+ years (senior level)
• Good knowledge of the Databricks platform
• Proficiency in SQL and Python
• Familiarity with at least one database engine: Oracle, PostgreSQL, or MS SQL
• Good understanding of basic data warehouse concepts: loading processes and layered architecture
• Knowledge of data modeling techniques (Kimball, Data Vault)
• Understanding of data testing approaches and experience with at least one tool like dbt tests or Great Expectations
• Understanding of data lineage and data cataloging concepts
• Practical knowledge of process orchestrators, e.g., Airflow, Dagster, or dbt
• Basic knowledge of Azure or AWS for data processing
• Ability to work with a Git repository
• Ability to create documentation for developed solutions
• Independence in managing own tasks, status, and priorities
• Curiosity in diagnosing data processing issues
• Openness to working with AI tools such as Claude or GitHub Copilot
• Willingness to understand business requirements beyond technology

Nice to have:

• Practical experience with dbt as a transformation tool beyond testing and with Databricks Asset Bundles (DAB)
• Basic understanding of data product concepts
• Knowledge of row-level and column-level security mechanisms and their implementation
• Familiarity with reference standards of selected domains: BIAN (banking), ACORD (insurance), HL7/FHIR (healthcare)