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Job Description Lead Data Engineer - IM Must Have Technical/Functional Skills Data Bricks , EBT ,Airflow , Asset Management exp Roles & Responsibilities Lead Data Engineer – Information Management (IM) Experience 8–15 Years ________________________________________ Role Overview We are looking for a highly skilled Lead Data Engineer with strong hands-on experience in Databricks, dbt, and Python, and a proven track record of leading and executing data platform migration and modernization programs. The ideal candidate will have experience migrating legacy data warehouses, ETL platforms, and cloud/on-prem data ecosystems to a modern Databricks Lakehouse architecture using dbt-based transformation frameworks. This is a hands-on leadership role requiring deep technical expertise, solution design capabilities, and the ability to mentor engineering teams while driving enterprise-scale data modernization initiatives. Key Responsibilities Data Engineering & Development Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, and Python. Develop and optimize ELT/ETL processes for large-scale data ingestion and transformation. Implement robust data quality, monitoring, and reconciliation frameworks. Build reusable data engineering components and frameworks. Data Platform Migration & Modernization Lead migration of legacy data platforms, data warehouses, and ETL ecosystems to Databricks Lakehouse. Transform existing ETL workloads to modern ELT patterns using dbt. Analyze source environments and define migration approaches, roadmap, and execution strategy. Drive code conversion, performance optimization, and workload modernization efforts. Databricks Engineering Develop Solutions Leveraging Databricks Lakehouse Platform Delta Lake Unity Catalog Databricks Workflows Structured Streaming Medallion Architecture (Bronze, Silver, Gold) Optimize Spark jobs and Databricks workloads for performance and cost efficiency. dbt Development Build and maintain dbt models, macros, tests, and documentation. Implement incremental processing and reusable transformation frameworks. Establish data lineage, testing, and CI/CD best practices. Work closely with business and analytics teams to build trusted datasets. Leadership & Collaboration Lead a team of data engineers and developers. Perform code reviews and enforce engineering standards. Collaborate with arch itects, product owners, business analysts, and stakeholders. Mentor junior engineers and drive adoption of best practices. Salary Range- $115,000-$170,000 a year
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.