Analytics Engineer - Data Warehousing (5-10 yrs)

About the role

In your role, you hold the responsibility of refining data at its source to facilitate seamless analysis, visualization, and utilization by data analysts, business stakeholders, and end-users alike.

As an analytics engineer, you not only handle the data itself but also manage its movement. Your proficiency extends to manipulating data through processes such as cleaning. conversion, and modeling.

Your primary task involves devising, refining, and implementing solutions that ensure data is acquired, refined, scheduled, and primed for analytical purposes.

Furthermore, as a senior figure within the Analytics Engineering domain, you play a pivotal role as a mentor, offering guidance and support to fellow engineers, both on an individual basis and within team settings.

Cross-Team Collaboration : You are responsible for collaborating with your data and engineering peers as well as collaborating with our other business teams to ensure the quality of the data that you are curating.

Responsibilities :

- Designing and building robust, Scalable and reusable data models in SQL that support a variety of downstream use cases, using tools like dbt.

- Configuring and optimizing aspects of a cloud data warehouse such as data permissions, compute and storage clusters, and table schemas

- Configuring data ingestion tools like Fivetran and its connectors to different data sources

- Designing and implementing data governance frameworks, such as data catalogs or data monitoring and observability platforms "Reviewing a teammate's or client's code for accuracy, DRYness, style and performance

- Cross-Team Collaboration

- Promotes a positive culture within and across different teams, collaborating with data engineers and data analysts on end-to-end Client requirements.

- Take initiative to identify and solve important problems.

- Coordinates with others on cross-cutting technical issues

Project Delivery :

- Optimizes for the predictability and regular cadence of deliverables.

- Keeps reliability, maintainability and scalability of systems

Skills & Qualifications :

Technical Skills :

- 4+ years of experience working with data warehouses.

- Proficiency in data warehousing, including expertise in ingestion methodologies and configuration of warehouse-specific feature

- Advanced proficiency in data modeling and transformation tools like dbt (3+ years of experience in dbt is a requirement with knowledge of integration patterns and orchestration platforms.)

- Strong programming skills, including version control and git proficiency.

- Deep understanding of domain-specific requirements, particularly in the financial sector.

Qualifications (Must Haves) :

- Demonstrated experience in data modeling for analytical purposes.

- Strong SQL programming skills.

- Extensive knowledge of data warehousing and ELT

- Hands on experience with data warehousing platforms such as snowflake, BigQuery, RedShift