Senior Data Analytics Engineer
Here is a comprehensive, professional job description template for a Senior Data Analytics Engineer ready to copy and paste into your posting:
Job Title: Senior Data Analytics EngineerLocation: New York, NY (Hybrid / Remote options)
Company: ApexCare Talent Solutions
Employment Type: Full-time
About the Role
We are seeking an experienced and business-minded Senior Data Analytics Engineer to join our growing data team. In this role, you will bridge the gap between raw data engineering and business intelligence. You will be responsible for designing, building, and maintaining robust data transformation pipelines, modeling clean datasets, and building analytics infrastructure that enables data-driven decision-making across the organization.
Key Responsibilities
Data Modeling & Architecture: Design, implement, and maintain scalable dimensional data models (star/snowflake schemas) in cloud data warehouses (Snowflake, BigQuery, Databricks, or Redshift).
Data Transformation & Pipelines: Build and maintain modern data transformation pipelines using dbt (data build tool), SQL, and Python, ensuring high reliability, testability, and version control.
Analytics & BI Development: Partner with stakeholders to translate business requirements into intuitive dashboards, reports, and self-service analytics frameworks using tools like Looker, Tableau, or Power BI.
Data Governance & Quality: Establish automated data testing, documentation, and monitoring protocols to maintain high standards of data quality, consistency, and integrity.
Performance Optimization: Monitor and optimize warehouse query performance, cost management, and data pipeline execution speed.
Cross-Functional Collaboration: Work closely with Data Engineers, Software Engineers, and Product Managers to integrate new data sources into the central warehouse.
Qualifications & SkillsExperience: 5+ years of experience in data analytics engineering, business intelligence, or data engineering roles.
SQL Mastery: Expert-level SQL skills for writing complex, optimized queries, transformations, and analytical functions.
Data Transformation: Strong, hands-on experience using dbt for modern data transformation and modeling.
Cloud Data Warehouses: Proven expertise with platforms like Snowflake, Google BigQuery, Amazon Redshift, or Databricks.
Programming: Proficiency in Python for data manipulation, automation, and custom ELT pipelines.
BI Tools: Advanced proficiency with enterprise BI platforms (Looker, Tableau, Power BI, Metabase).
Software Practices: Strong understanding of Git version control, CI/CD for data pipelines, and Agile development workflows.
Preferred QualificationsExperience with cloud orchestrators (Apache Airflow, Prefect, Dagster).
Familiarity with semantic layers (Cube, MetricFlow).
Background in health-tech, talent/recruiting systems, or high-growth SaaS environments.
What We OfferCompetitive salary and performance bonuses.
Comprehensive medical, dental, and vision health coverage.
401(k) retirement plan with company match.
Flexible work arrangements (Hybrid / Remote).
Paid time off (PTO) and continuous professional learning stipend.