Senior Analytics Engineer - ETL/Power BI (5-8 yrs)

As a Senior Analytics Engineer, you will play a critical role in designing, building, and maintaining our enterprise-level data and analytics infrastructure.

You'll collaborate with cross-functional teams, including product, engineering, and business operations, to ensure data quality and accessibility.

This role offers the opportunity to make a significant impact on our data strategy and influence product direction through data driven insights.

Responsibilities :

- Design & Implement Scalable Solutions: Architect and implement end-to-end analytics systems, including data ingestion, modeling, and visualization, ensuring robustness and scalability for large data volumes.

- Data Modeling & Pipeline Development: Create and maintain dimensional data models,build and optimize ETL/ELT pipelines, and automate reporting systems using modern data stack technologies (e.g., dbt, Airflow, Redshift, python, Sisense, Athena, Apache Iceberg).

- Collaborative Data Analysis: Partner with product teams to instrument and analyze user behavior data, translating business needs into technical requirements and delivering actionable insights.

- Data Quality & Monitoring: Implement rigorous data quality checks and monitoring frameworks to ensure data accuracy, reliability, and consistency.

- Documentation & Knowledge Sharing: Develop and maintain comprehensive documentation for data models, business logic, and analytical workflows.

Mentorship & Leadership: Guide and mentor junior engineers and analysts, fostering a culture of data engineering and analytics best practices.

Qualifications :

- 5+ years of experience in analytics/data engineering or similar roles within SaaS or enterprise settings.

- Advanced proficiency in SQL with proven experience in designing and implementing data models.

- Solid understanding of BI and visualization platforms (e.g., Looker, Sisense, Tableau,Power BI).

- Hands-on experience with dbt (or similar transformation tools) for data transformation and pipeline automation.

- Experience with cloud data warehouses such as Redshift, Snowflake, or BigQuery.

- Proficient in Python for data manipulation and analysis.

- Excellent communication and collaboration skills, with the ability to translate complex technical concepts to non-technical stakeholders.

Preferred Qualifications :

- Experience in modelling complex datasets for BI and analytics

- Experience with Airflow (or similar ETL tools).

- Experience with data governance and security best practices.

- Familiarity with real-time data streaming technologies (e.g., Kafka, Kinesis).

- Experience with machine learning and statistical modeling techniques.