Sr. Data Analytics Engineer

Primary Responsibilities

• Design and implement robust dimensional and relational data models that support analytical use cases for organizations across the business
• Build and maintain scalable dbt transformation pipelines, ensuring high data quality, performance, and cost-efficiency from raw ingestion to business-ready outputs
• Own the transformation and modeling of curated (Silver/Gold) datasets, ensuring clear contracts and traceability from raw to business-ready data.
• Collaborate with data analysts, product analytics, data scientists, and business stakeholders to translate requirements into durable data products that support experimentation, A/B testing, and advanced analytics
• Implement data quality tests, monitoring, SLAs, and alerting to ensure reliability of critical analytical datasets
• Partner with Data Engineers to define and enforce data contracts, ensuring schema stability and minimizing downstream breakage
• Follow analytics engineering best practices including version control, testing standards, and documentation
• Empower self-service analytics by building intuitive, well-documented data marts and semantic layers.

Qualifications

• Minimum 5+ years of experience in analytics engineering, data modeling, or similar roles working with enterprise-scale data, and demonstrated ownership of data products and cross-functional collaboration
• Expert-level SQL skills with deep understanding of query optimization and performance tuning
• Extensive experience with dbt (data build tool) including testing, documentation, and package management
• Strong programming skills in Python for data manipulation, automation, and custom analytics workflows
• Strong understanding of dimensional modeling, star schemas, one big table, and other data modeling methodologies
• Experience with modern cloud data warehouses (Snowflake, BigQuery, Redshift, or Databricks)
• Familiarity with orchestration frameworks (Airflow) and how analytics transformations are scheduled within broader data workflows
• Experience working with version control systems (Git) and implementing CI/CD for analytics code
• Strong business acumen and ability to translate business requirements into well-designed data models
• Understanding of data governance, privacy, and compliance requirements (GDPR, CCPA, and SOX)
• Familiarity with BI tools (Tableau, Looker, Mode, or similar) and how analysts consume data
• Strong ownership mindset with a passion for deeply understanding ambiguous business problems and translating them into clean, maintainable, and well-tested data models.
• Excellent communication skills with ability to explain technical concepts to both technical and non-technical audiences
• Dedication to data quality, documentation, and empowering others through self-service analytics