Senior Data Engineer: Lakehouse Architect & Platform Lead

As a Senior Data Engineer on the Analytics Platform, you will build and own the data foundation powering Novisto’s analytics, benchmarking, and AI products. You’ll design the lakehouse, data ingestion pipelines, and curated datasets while partnering with Tech Leads, Product Managers, and ESG Data Ops to turn raw operational data into reliable, well documented, query ready assets. The role combines hands on data engineering with strong software engineering practices, including data modelling, testing, CI/CD, version control, API and data contracts, and platform architecture, while balancing scalability, cost, freshness, and maintainability and mentoring developers on best practices.

What you’ll build and own:**

• Data Architecture & Lakehouse: Lead the design and evolution of Novisto's lakehouse, including storage layout, table formats, layering strategy, partitioning, and retention.
• Data Modelling & Ingestion: Model curated and semantic layers for analytics and reporting. Design batch, incremental, and CDC ingestion from all source modules, establishing clear data contracts.
• Pipeline Delivery & Execution: Build and operate robust ETL/ELT pipelines with clear ownership, dependency management, backfill strategy, and idempotent reprocessing. Contribute hands-on to transformation and orchestration codebases.
• Reliability & Observability: Build data quality tooling (schema validation, freshness/volume checks, automated regression tests) and platform observability (lineage, SLAs, alerting, cost telemetry). Own production health and incident response.
• Cross-functional Alignment: Write technical tickets to bridge functional intent and technical execution. Collaborate with Engineering Tech Leads and Principal Devs to ensure technical consistency, and mentor developers to grow data engineering capabilities across squads.
• Product Integration & Data Serving: Design and build the backend services and APIs that expose curated datasets to product modules. Implement multi-tenant data isolation, authentication and authorization (tenant scoping, row-level security), and serving patterns (query APIs, materialized views, caching) that meet product latency requirements.

Core Requirements

• Experience: 6+ years of data engineering or backend engineering experience, with 2+ years in a senior or lead capacity. Bachelor's degree in Computer Science or equivalent.
• Core Skills: Expert-level SQL and strong proficiency in Python. Familiarity with cloud infrastructure (Azure, GCP), CI/CD, containerization, infrastructure-as-code, and DevOps practices.
• Data Tech: Proven experience designing and operating a production lakehouse or cloud data warehouse (Databricks, Snowflake, BigQuery) with open table formats (Delta, Iceberg, Hudi). Hands-on experience with transformation frameworks (dbt) and orchestrators (Airflow, Dagster, Prefect).