{"id":68299,"url":"https://alion.io/job/patch-infotech-data-engineer-pharma-commercial-data","title":"Data Engineer - Pharma Commercial Data","company":{"id":1328,"name":"Patch Infotech","domain":"patchinfotech.com","url":"https://alion.io/company/patch-infotech","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, Pakistan"],"countries":["PK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Microsoft Fabric","optional":true},{"name":"Scrum","optional":true}],"status":"live","first_seen_at":"2026-08-21T07:12:47Z","employer_posted_date":null,"last_verified_at":"2026-08-21T07:12:47Z","board_verified":false,"closed_at":null,"days_open":57,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":57},"description":"We are seeking a skilled Data Engineer with strong expertise in SQL, Python, PySpark, ETL development, and Azure Databricks to design, build, and optimise scalable data pipelines. The ideal candidate should have hands-on experience working with pharmaceutical commercial datasets, including **claims, prescription (Rx), patient, sales, and payer data, and be proficient in processing large-scale healthcare data to support analytics and business intelligence initiatives.\nResponsibilities:\nDesign, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, and SQL.\nBuild and optimise data processing workflows in Azure Databricks.\nDevelop and maintain data ingestion frameworks from multiple structured and unstructured data sources.\nProcess and transform pharmaceutical commercial datasets, including claims, prescription, payer, sales, formulary, and patient-level data.\nOptimise Spark jobs for performance, scalability, and cost efficiency.\nImplement data quality checks, validation rules, and monitoring processes.\nCollaborate with business analysts, data scientists, and commercial analytics teams to deliver reliable datasets.\nDevelop reusable data engineering components and automation frameworks.\nTroubleshoot data pipeline issues and ensure high availability of data platforms.\nParticipate in code reviews and follow best practices for version control and CI/CD.\nEnsure compliance with healthcare data governance, privacy, and security standards.\nRequirements:\nStrong SQL programming and query optimisation skills.\nProficiency in Python for data engineering and automation.\nHands-on experience with PySpark and Apache Spark.\nExperience developing ETL/ELT pipelines.\nStrong experience with Azure Databricks.\nExperience with Azure Data Lake Storage (ADLS).\nKnowledge of Azure Data Factory (ADF) for orchestration.\nFamiliarity with Delta Lake, Parquet, and other big data storage formats.\nExperience with Git or Azure DevOps for source control.\nGood understanding of data modelling and data warehousing concepts.\nStrong analytical and problem-solving skills.\nBachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.\nDomain Expertise:\nExperience working with pharmaceutical commercial datasets is mandatory.\nHands-on knowledge of one or more of the following: Medical Claims Data, Pharmacy Claims Data, Prescription (Rx) Data, Patient-Level Data, Sales and Commercial Data, Payer and Formulary Data.\nUnderstanding of healthcare data standards and commercial analytics workflows is highly preferred.\nPreferred Qualifications:\nExperience with Azure Data Factory, Synapse Analytics, or Microsoft Fabric.\nKnowledge of Delta Live Tables and Databricks Workflows.\nFamiliarity with data governance and data catalogue tools.\nExperience with performance tuning for Spark workloads.\nExposure to Agile/Scrum development methodologies.\nHealthcare or Life Sciences industry experience.\nPreferred Certifications:\nMicrosoft Certified: Azure Data Engineer Associate.\nDatabricks Certified Data Engineer Associate/Professional.\nKey Competencies:\nStrong analytical and troubleshooting skills.\nExcellent communication and stakeholder management.\nAbility to work independently and collaboratively.\nAttention to detail and commitment to data quality.\nContinuous learning mindset and adaptability.","description_format":"text","description_chars":3344,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Mobile App Development Services","Web Development Services","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-08-21T07:12:47Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long 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