Data Analytics Engineer

NO C2C, NO THIRD PARTY VENDORS, NO SPONSORSHIPS

We are seeking a dynamic and detail-oriented Lead Data Engineer – Business Analytics to join our team. This role is responsible for designing, building, and optimizing analytics-ready datasets within a modern data platform leveraging Databricks. The ideal candidate will serve as a bridge between data engineering and business analytics—transforming raw, disparate data into trusted, performant, and governed datasets that enable enterprise reporting and self-service analytics. This role will focus on developing and maintaining curated Silver and Gold layer data assets within a medallion architecture, where the semantic layer resides in Databricks rather than BI tools. You will partner closely with business stakeholders, data architects, and analytics teams to ensure alignment with business logic, KPIs, and enterprise data standards.

Key Responsibilities:

Data Engineering & Modeling

- Design, build, and maintain scalable data pipelines and curated datasets within the Databricks Lakehouse (Silver and Gold layers).

- Develop and manage analytics-ready data models and semantic structures in Databricks, aligned to enterprise reporting needs.

- Transform raw data into business-consumable datasets that reflect standardized definitions, KPIs, and metrics.

- Apply dimensional modeling and other data modeling techniques within a distributed data environment.

Semantic Layer & Analytics Enablement

- Own the semantic layer within Databricks, ensuring consistent definitions across reporting and analytics use cases.

- Enable downstream consumption by visualization and analytics tools (e.g., Power BI) without reliance on embedded semantic modeling.

- Partner with business analysts and reporting teams to optimize datasets for usability, performance, and scalability.

Performance Optimization & Data Quality

- Optimize datasets and data models for performance, including query efficiency and scalability for enterprise reporting workloads.

- Ensure data quality, integrity, and consistency across the full data lifecycle.

- Implement and enforce data governance standards, including data security, masking, access controls and cost controls.

Collaboration & Business Alignment

- Work closely with business leaders and stakeholders to translate business requirements into scalable data solutions.

- Align data structures to enterprise data dictionary and KPI definitions.

- Communicate data model designs and dataset structures clearly to both technical and non-technical stakeholders.

Platform & Modernization

- Support the evolution of the enterprise analytics platform within Azure and Databricks.

- Contribute to best practices for CI/CD, deployment automation, and data engineering standards.

- Assist in advancing data capabilities, including support for AI/ML use cases where applicable.

Qualifications

- Bachelor’s degree in Information Technology, Computer Science, Business Analytics, or a related field.

- 6 years of experience in data engineering, data modeling, or analytics engineering roles.

- Strong expertise in Databricks Unity Catalog, SQL, and Python for data transformation and pipeline development.

- Proven experience designing and implementing data models within modern data platforms (e.g., Lakehouse architecture).

- Experience working with medallion architecture (Bronze/Silver/Gold layers).

- Understanding of BI tools (e.g., Power BI), with emphasis on dataset consumption rather than semantic layer ownership.

- Experience with CI/CD pipelines, version control, and deployment processes.

- Familiarity with Agile/Scrum delivery methodologies.

Skills and Competencies

- Strong data modeling and analytical thinking skills.

- Ability to translate business requirements into scalable data solutions.

- Deep understanding of data transformation, optimization, and performance tuning.

- Excellent communication and stakeholder management skills.

- High attention to detail with a focus on data accuracy and quality.

- Ability to lead initiatives and influence cross-functional teams.

- Adaptability in a fast-paced, evolving data environment. Working Conditions This position may require occasional travel. Flexible work hours may be necessary to meet project deadlines.

Working Conditions

•             This position may require occasional travel.

•             Flexible work hours may be necessary to meet project deadlines