Data Analytics Engineer  

Roles and Responsibilities

1. SQL Proficiency for Analytics

○ Writes optimized queries to support BI workloads.

○ Uses window functions, CTEs, and subqueries for analytical transformations.

○ Tunes queries with a focus on speed for dashboards and reporting.

○ Adapts across SQL dialects (PostgreSQL, BigQuery, Snowflake, etc.).

2. Data Modeling G Warehousing

○ Designs star/snowflake schemas for BI use cases.

○ Balances Kimball (analytics-oriented) and Inmon (integration) approaches.

○ Optimizes partitioning and clustering for query efifiiciency (rather than compute efficiency).

3. BI Readiness G Reporting Support

○ Builds curated datasets for BI tools (Looker, Tableau, Power BI).

○ Collaborates with analysts to ensure usability of datasets.

4. Data Quality G Validation

○ Implements automated testing in dbt or similar.

○ Familiarity with observability tools.

○ Ensures trustworthiness of analytics-layer tables.

5. Pipeline Development (Analytics-Focused)

○ Orchestrates workflows with dbt, Airflow, or Fivetran.

○ Manages ELT with emphasis on transfiormation in the warehouse.

6. Governance G Privacy (User-Facing Data)

○ Implements data masking and role-based access control for analysts.

○ Ensures compliance at the analytics layer.

Education & Experience:

● Bachelorʼs degree in Business, Data Science, Information Systems, or related field; Masterʼs preferred

● 3-5 years of experience in business analysis, data/analytics, or consulting roles with increasing scope

● Experience leading cross-functional data initiatives across multiple domains (e.g., marketing, operations, finance)

Preferred Certifications:

Data visualization or analytics platform certifications (Google Data Analytics Professional Certificate, Power BI Data Analyst Associate, Tableau Desktop Specialist, etc.)

Data storytelling, product thinking, or stakeholder engagement training is a plus