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Designation : Technical Lead Data Engineer (Databricks) Location : Hyderabad (Hybrid) Experience : 12+ years Role Overview : We are seeking a Senior Technical Leader to provide hands-on technical leadership for clinical data engineering, data platform development, and analytics delivery. This role will lead the design and execution of scalable data pipelines, lakehouse architecture, cloud services integration, and delivery governance across active clinical data initiatives. The ideal candidate will have strong experience with Databricks Lakehouse, Delta Lake, Unity Catalog, Medallion architecture, SQL Warehouses, AWS services, data engineering delivery, agile execution, and stakeholder management in a life sciences or regulated data environment. Key Responsibilities : - Serve as the technical lead for clinical data engineering and platform delivery. - Own architecture and implementation across Databricks Lakehouse, Delta Lake, Unity Catalog, Medallion architecture, and SQL Warehouses. - Lead end-to-end delivery of data pipelines, curated datasets, data products, and analytics-ready data assets. - Manage and guide a team of 5 to 10+ data engineers across onsite and offshore delivery. - Provide technical direction on pipeline design, data modeling, performance optimization, security, scalability, and production readiness. - Work with AWS services such as S3, EMR/Athena, Secrets Manager, IAM, and related cloud platform components. - Drive sprint planning, backlog management, technical design reviews, code reviews, release planning, and delivery governance. - Partner with Clinical Operations, Biostatistics, Data Management, IT, data managers, and business stakeholders to translate requirements into technical solutions. - Coordinate cross-functional delivery across data engineering, analytics, AI/ML, platform, QA, and business teams. - Ensure engineering outputs meet quality, security, compliance, performance, and maintainability expectations. - Support issue resolution across data ingestion, transformation, pipeline failures, data quality defects, and platform dependencies. - Provide technical oversight for automation, AI/ML-enabled workflows, and human-in-the-loop data operations where applicable. Required Qualifications : - 12+ years of experience in data engineering, data architecture, analytics engineering, or cloud data platform delivery. - Strong hands-on experience with Databricks Lakehouse, including : 1. Delta Lake 2. Unity Catalog 3. Medallion architecture 4. SQL Warehouses 5. Notebook/job orchestration 6. Data pipeline performance tuning - Working knowledge of AWS services including S3, EMR/Athena, Secrets Manager, IAM, and cloud-native security patterns. - Proven experience leading 510+ data engineers and owning end-to-end technical delivery. - Strong understanding of data pipeline design, batch processing, data transformation, data modeling, and analytics enablement. - Experience with agile delivery, sprint ceremonies, backlog management, release management, and technical execution governance. - Ability to work in cross-functional delivery models involving technical teams, business users, data managers, and client stakeholders. - Strong stakeholder management and client-facing communication skills. - Ability to translate business and clinical data requirements into scalable technical architecture and implementation plans. Preferred Qualifications : - Experience in pharma, biotech, CRO, clinical operations, or life sciences data environments. - Familiarity with clinical data domains, study data, lab data, safety data, EDC data, or biostatistics workflows. - Experience working with AI/ML, automation, or metadata-driven data pipelines. - Knowledge of data governance, data quality, lineage, auditability, and regulated data controls. - Experience with CI/CD, Git-based development, DevOps practices, and production support models. - Experience managing distributed onsite/offshore delivery teams .
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.