Data Engineer I

Hyderabad, INPosted Jul 3, 2026
Career Areas Career Stories Join Talent Community Candidate Login English English Italiano Español Français Português Norsk Deutsch 日本語 Bahasa melayu 中文 (简体) 中文 (繁體) 한국어 ภาษาไทย Nederlands Polski Yкраїнська Hrvatski Ελληνικά Magyar čeština Türkçe Pусский Haitian עברית Brazilian Português Dansk Suomi Svenska Français (Canada) Português (Portugal) Careers Home Life at BMS Career Areas Student Opportunities Events How We Recruit Career Stories Search this site Join Talent Community Candidate Login English English Italiano Español Français Português Norsk Deutsch 日本語 Bahasa melayu 中文 (简体) 中文 (繁體) 한국어 ภาษาไทย Nederlands Polski Yкраїнська Hrvatski Ελληνικά Magyar čeština Türkçe Pусский Haitian עברית Brazilian Português Dansk Suomi Svenska Français (Canada) Português (Portugal) Single PositionView All JobsHybridData Engineer IHyderabad - TS - IN No longer accepting applications.Job IDR1601482Date posted04/15/2026DepartmentNot ApplicablePosition SummaryWe are looking for an early‑career Data Engineer to help build, operate, and continuously improve reliable data pipelines and curated datasets that support commercial analytics and reporting. In this role, you will transform raw data into high‑quality, analytics‑ready tables in the refined layer, applying data modeling best practices, validation checks, and governance standards. You will work closely with engineers, analysts, and business stakeholders to understand data requirements, implement scalable transformations, and ensure data products are trusted, secure, and well‑documented.Key Responsibilities·       Design, build, and support reliable batch and incremental data pipelines for commercial data products, ensuring scalability, maintainability, and operational readiness.·       Ingest, transform, and integrate large-scale structured and semi-structured pharma datasets (e.g., claims, patient, HUB, and specialty pharmacy data) into curated refined-layer tables.·       Implement transformation logic including cross-domain joins and slowly changing dimensions (SCD) and maintain clear technical documentation for datasets and pipelines.·       Ensure data quality through cleansing, standardization, deduplication, reconciliation, automated validation checks, anomaly detection, and monitoring/alerting; triage and resolve data issues.·       Apply data governance practices including documentation, lineage, access controls, and compliant handling of sensitive/regulated data.·       Partner with analysts and business stakeholders to translate requirements into data specifications, define dataset readiness criteria, and support adoption of published data products.Skills & CompetanciesProficiency in SQL and Python for data transformation, validation, and pipeline development.Experience building ETL/ELT pipelines and working with lakehouse concepts (e.g., medallion architecture; bronze/silver/gold layers).Hands-on experience with Databricks (notebooks/jobs/workflows) and Delta Lake concepts (ACID tables, incremental processing, upserts/merge).Familiarity with data modeling for analytics-ready datasets.Experience with cloud data engineering fundamentals (e.g., AWS storage/compute, IAM concepts)Understanding of data quality practices and operational support.Working knowledge of engineering best practices (Git/version control, code reviews, basic CI/CD concepts).Understanding of data governance and secure data handling (documentation, lineage, access controls, PII/PHI awareness).Familiarity with BI/visualization tools (Tableau/Power BI) is a plus for downstream consumption.Strong problem-solving, communication, and time-management skillsAbility to work with both technical and business partners.Qualifications & ExperienceBachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Statistics/Mathematics, or a related field (or equivalent practical experience).1–3 years of hands-on experience in data engineering or related roles, building and supporting ETL/ELT pipelines and...

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