{"id":3791795,"url":"https://alion.io/job/procdna-analytics-india-cloud-data-engineer-procdna","title":"[India] - Cloud Data Engineer - ProcDNA","company":{"id":4465837,"name":"Procdna Analytics","domain":"procdna.com","url":"https://alion.io/company/procdna-analytics","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"AWS Glue","optional":true},{"name":"Databricks","optional":true}],"status":"live","first_seen_at":"2026-11-05T07:00:56Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-07T03:47:40Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About ProcDNA\nProcDNA is a global consulting firm. We fuse design thinking with cutting-edge technology to create game-changing Commercial Analytics and Technology solutions for our clients. We're a passionate team of 475+ across 9 offices, all growing and learning together since our launch during the pandemic. Here, you won't be stuck in a cubicle - you'll be out in the open water, shaping the future with brilliant minds. At ProcDNA, innovation isn't just encouraged; it's ingrained in our DNA. Ready to join our epic growth journey?\nWhat we are looking for\nLooking for a motivated Cloud Data Engineer with 5-7 years of experience to design, develop, and maintain scalable data pipelines and cloud-based platforms. Hands-on experience with AWS or Azure, along with strong programming skills in Python and SQL, and a solid understanding of ETL/ELT processes, data warehousing, and data modeling is essential. Experience with orchestration, exposure to batch or real-time processing, and familiarity with CI/CD, Git, and basic DevOps/DataOps practices is desirable. Strong communication skills, a collaborative mindset, and the ability to work effectively with cross-functional teams are key expectations.\nWhat you'll do\nDesign, develop, and maintain scalable ETL/ELT pipelines using Databricks and cloud platforms (AWS/Azure).\nImplement data transformation logic, validation rules, and data quality checks to ensure accuracy, consistency, and reliability of datasets.\nDevelop and manage data models, schemas, and data warehouse structures to enable seamless data consumption for analytics and reporting.\nMonitor, troubleshoot, and continuously optimize data pipelines for performance, scalability, reliability, and cost efficiency in cloud environments.\nEnsure adherence to data governance, security, and compliance standards across all data processing and storage layers.\nCollaborate closely with cross-functional teams to deliver scalable, high-quality, and business-aligned data solutions.\nMust Have\nMinimum 5-7 years of experience in a Data Engineering role with a B.Tech/BE or equivalent technical background.\nStrong programming skills in Python and SQL with experience in building and optimizing data pipelines.\nHands-on experience building ETL/ELT pipelines and cloud data services (Azure or AWS).\nExperience working with Databricks or similar distributed data processing frameworks (e.g., AWS Glue).\nFamiliarity with workflow orchestration tools like Airflow and version control systems such as Git.\nExperience handling large datasets, implementing data quality checks, and understanding data ingestion, storage, and consumption architectures.\nGood understanding of data quality, monitoring, and basic DevOps/DataOps practices, along with strong problem-solving and communication skills.\nClient and Stakeholder management along with Team Management experience is 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