Description :

As a Senior Data & Analytics Engineer, you will be a key technical contributor who designs and builds both data infrastructure and analytics-ready data models.

You will develop and maintain data pipelines and transformation layers that enable self-service analytics across the organization.

You will partner closely with business stakeholders, analysts, and data scientists to understand requirements and translate them into scalable, well-modeled data products.

You will design for data integrity, reliability, and performance while ensuring data is accessible, documented, and trustworthy for downstream consumers.

You will contribute to code quality through adherence to standards and participation in peer code and architecture reviews.

What You'll Need :

5+ years hands-on experience with a combination of :

- SQL mastery including writing complex, highly-optimized queries and designing dimensional data models.

- Expert-level analytical SQL (window functions, CTEs, pivots, advanced joins).

- Building reusable, parameterized logic for transformations.

- Writing testable, modular SQL models (dbt or equivalent).

- Translating ambiguous business questions into structured data models and metrics.

- Designing semantic layers, metrics, and business logic for analytics consumption.

- Python software development for data pipelines and automation.

- Building and maintaining data transformation pipelines using tools like dbt, SQL, and Python.

- Integration with Business Intelligence tools (e.g., Looker, QuickSight, Tableau).

- Building and maintaining data integration (ETL/ELT) pipelines using SQL, EMR, Python and Spark.

- Good to have knowledge on ETL/ELT with batch (AWS Data Pipeline, Airflow) and streaming (Kinesis, Kafka).

- Creating scalable, well-documented data models following dimensional modeling best practices.

- Experience with modern analytics engineering tools and practices (e.g., dbt, data modeling, testing frameworks, version control for analytics code).

- Experience using tools like Cursor/ChatGPT to speed up coding and testing, improve documentation, and raise code quality (maintainability, readability, security, performance) is strongly preferred.

- Strong understanding of data modeling concepts (star schema, dimensional modeling, slowly changing dimensions).

- Experience working with data lakes and contributing to automation and simplification improvements across the data ecosystem.

- Experience owning features from design through delivery along with ongoing support.

- Strong ability to communicate effectively with both technical and non-technical stakeholders, translating business requirements into technical solutions.

- Experience partnering with analysts, data scientists, and business teams to define metrics, KPIs, and reporting requirements.

- Experience mentoring junior engineers and analysts, and promoting best practices for data management, quality, and governance.

- Undergraduate or graduate degree in Computer Science, Information Systems, or related field.

Experience with the following will be added advantage :

- Working with columnar databases (e.g., Redshift, Snowflake) and optimizing for query performance.

- Distributed data processing (Hadoop, Spark, Hive).

- Extra consideration will be given to those with Healthcare-relevant company experience, with demonstrated industry knowledge of handling sensitive information.