Data Architect/Tech Lead

Department: Data Analytics
Experience: 8–10 years
Location: Ahmedabad/ Remote
About Simform:

Simform is a premier digital engineering company specialising in Cloud, Data, AI/ML, and Experience Engineering to create seamless digital experiences and scalable products. Simform has strong capabilities across Microsoft, AWS, Google Cloud, and Databricks. With a presence in 6 countries, Simform primarily serves North America, the UK, and the Northern European market. Simform is well-recognised as one of the most reputed employers in the region, having created a thriving work culture with a high work-life balance that gives a sense of freedom and opportunity to grow.

You will lead a small delivery pod building modern data platforms on Microsoft Fabric and Azure for global clients — from discovery and architecture through to production hand-over. This is a hands-on lead role: roughly 60% architecture and build, 40% technical leadership, code review, and client-facing communication. It is positioned as an entry point into our Data Architect track, so the person who does this well grows into owning platform architecture across multiple accounts.

• Design end-to-end lakehouse/medallion architectures on Microsoft Fabric — OneLake, Lakehouse/Warehouse, Data Factory pipelines, Dataflows Gen2, Notebooks (PySpark), and Direct Lake semantic models.

• Own technical decisions on a project: storage layout, ingestion patterns, orchestration, incremental load strategy, capacity sizing (F-SKUs), and cost/performance trade-offs.

• Lead a team of 3–6 data engineers and BI developers — task breakdown, estimation, PR/peer reviews, and quality gates.

• Translate client requirements into architecture and estimates; participate in discovery workshops and technical presales conversations.

• Implement data governance and security: workspace and RBAC design, row-level security, sensitivity labels, lineage and cataloguing (Microsoft Purview), data quality rules.

• Set up CI/CD and environment promotion using Fabric deployment pipelines, Git integration, and Azure DevOps.

• Establish and enforce engineering standards — naming conventions, documentation, reusable frameworks, testing.

• Mentor engineers and contribute to internal capability building, POCs, and reusable accelerators.

• 8–10 years in data engineering/analytics, with at least 2 years hands-on on Microsoft Fabric in a production (not POC-only) capacity.

• Strong Azure data stack: Azure Data Factory / Synapse, Azure Data Lake Storage Gen2, Azure SQL, Key Vault, and an understanding of networking basics (VNet, private endpoints, gateways).

• Advanced SQL and solid Python/PySpark for transformation at scale.

• Dimensional modeling depth — star schema, SCDs, conformed dimensions — and the judgment to know when to break the rules.

• Power BI semantic modeling: DAX, composite/Direct Lake models, performance tuning, deployment pipelines.

• Data governance exposure: Microsoft Purview or Atlan/Collibra — catalog, lineage, classification, data quality.

• Demonstrated technical leadership: has led a team or workstream, reviewed others' code, and been accountable for delivery quality.

• Clear written and spoken English; comfortable presenting a design to a client architect and defending it.

• Hands-on Databricks or Snowflake (Unity Catalog, Delta Lake, dbt) — we run multi-platform engagements and cross-platform fluency is valued.

• dbt, Dagster, or similar transformation/orchestration frameworks.

• Real-time/streaming: Fabric Real-Time Intelligence, Event Streams, KQL.

• Migration experience: on-prem SQL/SSIS, Synapse, or Tableau → Fabric/Power BI.

• Exposure to Fabric Copilot / Data Agents or AI-on-lakehouse patterns.

• Certifications: DP-600 / DP-700, DP-203, or Azure Solutions Architect.

• Takes ownership of outcomes, not just tickets.

• Explains trade-offs in business terms, not only technical ones.

• Comfortable with ambiguity — client requirements arrive incomplete, and we expect you to ask the right questions rather than wait.

• Genuinely enjoys mentoring; the team's growth is part of the job description, not a side effect.