Job Description
Responsibilities
- Own end-to-end ETL/ELT pipelines: ingestion → transformation → modeling → serving.
- Lead dbt : project architecture, macros, tests, docs, CI/CD, performance, and standards.
- Build dimensional models (star/snowflake), conformed dimensions, SCD patterns, deduping/record selection, KPI/metric consistency.
- Deliver production-grade data: monitoring, lineage, alerting, SLAs, and cost/performance optimization.
- Build tooling and automation in Python ; enable ML/AI datasets and feature-ready pipelines.
- Mentor engineers, conduct reviews, and drive best practices.
- Stay current with modern data/AI tech; recommend and adopt what meaningfully improves outcomes.
Requirements
- 5-8 years in Data Engineering; Proven ability to lead in a fast-paced environment : Ownership mindset, bias to action, comfort with ambiguity, strong communication.
- Strong dbt expertise in production environments (models, macros, testing, docs, CI/CD).
- Excellent data modeling skills (dimensional modeling, SCD, grain, conformed dimensions, metric definitions).
- Advanced SQL : query optimization, warehouse performance tuning, incremental strategies.
- Strong Python for data engineering (automation, pipelines, packaging, quality checks).
- Working knowledge of ML/data science workflows
About Analyttica
Analyttica partners with enterprises on complex digital and data transformation journeys. We start with diving deep into enterprise business context - industry, products, processes, and people. We then use the right mix of business consulting, Data & AI solutions, and our flagship product (LEAPS) to modernize data foundations, deliver decision-ready analytics, and scale data literacy across teams.
Culture & Values
We’re a lean, fast-paced, and collaborative team driven by our common goal of pushing the boundaries of what’s possible with data and AI. Curiosity, honesty, and ownership sit at the core of how we work. We give people the space and freedom to design, build, and refine solutions end-to-end - and to grow as they do it.
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