{"id":2721609,"url":"https://alion.io/job/merck-co-dir-data-engineering","title":"Dir , Data Engineering","company":{"id":3768,"name":"Merck & Co.","domain":"msd.com","url":"https://alion.io/company/msd","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":244,"ghost_share":0.012,"stale_share":0.061,"repost_share":0.09,"time_to_fill_p50_days":12,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":32000,"max_usd":59000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":10,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Neptune","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab CI","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kanban","optional":false},{"name":"Kubernetes","optional":false},{"name":"Matillion","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-16T15:02:10Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-16T20:07:39Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Description\nWhat will you do in this role:\nPartner with colleagues in scientific data product line and stakeholders to understand the data priorities in support of research outcomes\nPartner with engineering teams in scientific data product line to understand and influence architectural choices and talent needs\nDefine/Influence engineering squad configuration in collaboration with product manager and product tech lead to support roadmap objectives for products in Scientific Data Product Line\nProvide leadership to engineering squads in Hyderabad Tech Center (HTC) to design/engineer and implement data product features in support of research\nDefine and implement data engineering strategies that align with organizational goals and data governance standards. \nConnect with external partners and thought leaders to stay current on the latest technologies and trends in Data Engineering. \nEvaluate and introduce new technologies, tools, and frameworks that enhance productivity and data quality.\nConduct regular 1:1s, performance reviews, career development planning, and succession planning.\nIn collaboration with Scientific Data product Line leader and product line technical leader, understand current and future engineering talent needs\nDrive recruitment, onboarding, and retention of top data engineering talent.\nDevelop and execute a learning roadmap for the engineering team in Tech Center (training, certifications, communities of practice, internal tech talks).\nFoster a culture of learning, innovation, psychological safety, and knowledge sharing.\nUnderstand the purpose of our company and role of research and research IT in support of this purpose\nBe an ambassador to help the team and broader HTC community understand and internalize this purpose\nWork with other engineering leaders in HTC to develop and participate in a community to learn engineering practices from each other\nLeverage enterprise engineering tools and processes and be an advocate for them in the team and beyond. Actively provide feedback to enterprise teams to evolve these tools and processes in support of research engineering needs\nWhat Should you have:\n\nQualifications\nEducation & Experience\n\nBachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Mathematics, or related field; or equivalent experience.\nTypically, 10+ years of experience in data engineering or related roles, with 5+ years in a leadership, lead engineer, or chapter/people lead capacity.\nProven track record building and maintaining large-scale data platforms and pipelines in complex enterprise environments.\n\nTechnical Skills\nStrong hands-on experience with modern data engineering technologies, such as:Programming: Python, Java, SQL\nData processing: Spark, Databricks, dBt, Matillion\nData warehousing / Lakehouse: Delta Lake, Redshift, Neptune\nCloud platforms: AWS (preferred)/ Azure\nStreaming: Kafka, Kinesis, Pub/Sub, Event Hubs, etc.\n\nSolid understanding of:ETL/ELT concepts\nData quality, metadata management, and observability\nCI/CD, Infrastructure as Code, and containerization (e.g., GitHub/GitLab CI, Jenkins, Terraform, Docker, Kubernetes)\nSecurity, privacy, and compliance concepts (e.g., RBAC, encryption, PII handling).\n\nLeadership & Soft Skills\n\nDemonstrated ability to lead and grow technical teams and communities in a product team environment.\nStrong coaching and mentoring skills; able to develop both technical and behavioral capabilities.\nStrategic mindset with the ability to balance long-term architecture with short-term delivery needs.\nExcellent communication and influencing skills, with experience of engaging senior stakeholders.\nComfortable working in agile environments (Scrum/Kanban) and applying product centric ways of working.\nAdditional location(s) Compensation Information:\nRequired Skills:\nAmazon Web Services (AWS), Amazon Web Services (AWS), Apache Kafka, Business Intelligence (BI), Computer Science, Database Administration, Databricks Unified Data Analytics Platform, Data Engineering, Data Lake, Data Management, Data Modeling, Data Pipelines, Data Processing, Data Store, Data Visualization, Design Applications, Docker Container, Engineering Leadership, GitHub, Information Management, Knowledge Sharing, Metrics Development, Personally Identifiable Information (PII), Product Roadmap, Python (Programming Language) {+ 5 more}Preferred Skills:\nCurrent Employees apply HERE\nCurrent Contingent Workers apply HERE\nSecondary Language(s) Job Description:\n#MSDHYDIT\nSearch Firm Representatives Please Read Carefully\nMerck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.\nEmployee Status:\nRegularRelocation:\nVISA Sponsorship:\nTravel Requirements:\nFlexible Work Arrangements:\nHybridShift:\nValid Driving License:\nHazardous Material(s):\nJob Posting End Date:\n10/31/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. 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