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We are building a fast-growing Databricks practice delivering enterprise data and AI solutions across APAC. As Lead Solution Architect - Data Engineering, you will be the technical anchor of the practice: leading solution design on client engagements, owning and defending enterprise architectures in presales, and driving large-scale migration and cloud transformation programs. This is a hands-on leadership role for a builder who can equally command a whiteboard in front of a CTO and a Spark UI when a pipeline misbehaves. You will also shape the practice itself — mentoring engineers, creating accelerators and reusable assets, and converting delivery success into case studies and go-to-market offerings. Architecture & Delivery Own end-to-end architecture and design decisions on Databricks engagements, ensuring solutions are secure, scalable, performant, and aligned with Lakehouse best practices Lead delivery of production-grade data platforms — ingestion, transformation, orchestration, governance through Unity Catalog, and downstream BI/ML enablement Lead large-scale migrations (legacy DW/ETL, Hadoop, on-prem estates) and cloud transformation projects to Databricks on Azure/AWS/GCP, including assessment, wave planning, and cutover Stay hands-on: performance tuning, debugging, code and design reviews, and setting engineering standards for the team Presales & Stakeholder Management Own and defend enterprise solution designs in front of architecture boards, CIOs, and CTOs — and enjoy it Drive presales end-to-end: discovery, solutioning, estimation, PoCs, RFPs, and proposals that convert Translate hard technical trade-offs into decisions executives can act on — from engineer to boardroom without changing gears Who Thrives Here A builder at heart — 12+ years in data engineering/architecture, 3+ on Databricks at enterprise scale, and still happiest when hands are on the keyboard Deep Spark expertise — architecture, performance tuning, streaming, debugging, the advanced stuff that separates architects from diagram-drawers Lakehouse fluency — Medallion architecture, Delta Lake, Unity Catalog, governance, orchestration (Workflows, DLT/Lakeflow, Airflow, ADF); Microsoft Fabric exposure a bonus Battle-tested in migrations — you've led large transformation programs and have the scars and success stories to show for it Presales instinct — you don't just design solutions; you sell them, price them, and defend them under fire Modern edge — strong Python/SQL/Scala, CI/CD for data platforms, and comfort integrating ML/AI (MLflow, LLM APIs like OpenAI and Anthropic) into what you build Certified credibility — Databricks Data Engineer Professional / SA accreditations strongly preferred Founder energy — curiosity, adaptability, and the drive to build offerings, not just deliver projects
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.