{"id":1958690,"url":"https://alion.io/job/zifo-senior-clinical-data-engineer","title":"Senior Clinical Data Engineer","company":{"id":686878,"name":"Zifo","domain":"zifo.com","url":"https://alion.io/company/zifo","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":83,"open_postings":9,"ghost_share":0,"stale_share":0.667,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-13T05:45:00Z"}},"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":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":55},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-06T14:22:38Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-13T15:15:26Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"We are looking for an experienced Senior Clinical Data Engineer to design, build, and manage scalable data pipelines supporting clinical trials.\nIn this role, you will be responsible for the end-to-end ingestion, integration, transformation, and delivery of clinical data from multiple source systems into enterprise data platforms such as data lakes and data warehouses. You will work closely with clinical data teams, analytics teams, and other downstream consumers to ensure that clinical data is reliable, traceable, high quality, and ready for use.\nRequirements\nBachelor's degree (BE/BTech/BS/BA) in Computer Science, Information Technology, Engineering, Life Sciences, Health Sciences, or a related discipline.\n5+ years of experience in Data Engineering, Software Engineering, or a related technology role.\nStrong hands-on programming experience with Python and SQL.\nHands-on experience with AWS cloud platform.\nExperience designing and deploying production-grade ETL/ELT data pipelines in cloud environments.\nHands-on experience with distributed/big-data processing technologies such as Apache Spark.\nExperience with workflow orchestration and scheduling using Apache Airflow.\nExperience working with data lakes and/or cloud data warehouses, such as Snowflake or Amazon Redshift.\nStrong understanding of database concepts, data modeling, data integration, and large-scale data processing.\nExperience handling semi-structured data formats such as JSON and XML.\nExperience building or consuming REST/API-based integrations.\nFamiliarity with source control and CI/CD tools such as GitLab/GitHub.\nStrong understanding and practical application of the Software Development Life Cycle (SDLC).\nClinical Domain Experience\nExperience working with clinical trial data and clinical data workflows.\nFamiliarity with clinical systems and data sources such as EDC/eCRF, CTMS, and other clinical trial source systems.\nAbility to understand study-level data requirements and translate them into scalable technical solutions.\nExperience coordinating or supporting study-level data transfer and integration specifications is preferred.\nUnderstanding of data quality, traceability, validation, and regulatory expectations within a clinical environment is highly desirable.\nKey Competencies\nStrong analytical and critical-thinking skills.\nExcellent problem-solving and troubleshooting abilities.\nAbility to independently own technical deliverables while working effectively within cross-functional teams.\nStrong communication skills with the ability to collaborate with both technical and clinical stakeholders.\nAbility to understand complex data requirements and translate them into practical engineering solutions.\nStrong focus on data quality, reliability, scalability, and automation.\nAbility to manage priorities and deliver within clinical study timelines.\nTechnology Landscape\nProgramming: Python (Advanced)\nBig Data: Apache Spark\nOrchestration: Apache Airflow\nCloud: AWS\nData Platforms: Amazon Redshift / Data Lakes\nDatabases: SQL\nData Integration: REST APIs, JSON, XML, file-based integrations\nDevOps: GitLab / GitHub, CI/CD\nClinical Systems: EDC/eCRF, CTMS, clinical source 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