Role Description We are actively seeking an MDM Informatica C360 with Data Engineer for one of our clients. - Posting Title: Informatica C360 Developer with Data Engineering - Primary Skills: Informatica C360, Python, Hadoop, SQL - Details of the application, domain, as appropriate: - Design, develop and maintain the MDM solution using Informatica MDM C360 - Configure MDM entities, schema, systems and trust settings in HUB - Create/update match and merge rules for different business groups/organizations - Integrate the MDM solution with other enterprise systems - Develop custom scripts in Python to support data processing and analysis - Implement data processing workflows using Hive - Write complex SQL queries and optimize database performance for efficient data processing - Troubleshoot and debug issues related to MDM, data pipelines, workflows, and ETL processes - Perform testing and debugging of code to ensure high quality deliverables - Provide support for MDM Data Model and C360 Implementation to customers, business, and cross-functional partners - Key responsibilities and expected output: - Interface with business and IT stakeholders to gather requirements, create user stories and validate the same - Work with data engineers to explain data engineering requirements - Design, Development, Testing, and rollout of Tableau Dashboards Qualifications - Bachelor's degree in Computer Science, Software Engineering, or related field - Minimum 5 years of experience with Informatica MDM Customer C360 - Experience with Python or other scripting languages - Minimum 2 years of experience in data warehousing and analysis using Hive - Experience working with big data technologies such as Hadoop, Spark, and Kafka - Strong SQL skills - Excellent problem solving and debugging skills Requirements - Familiarity with data governance and data management best practices - Experience with data visualization tools such as Tableau, Power BI, or QlikView Any other information considered "critical" / "Useful" We are seeking an experienced Informatica C360 Developer with strong data engineering skills to join our team. The ideal candidate will be responsible for designing, developing, testing, and maintaining data pipelines and workflows in Informatica C360 (Customer 360), as well as leveraging Hive for data. Work Experience - 5 years Mode of Engagement - Managed Services

• Build AI-powered tools and data infrastructure • Develop full-stack applications bridging AI, data, and user needs • Create Slack-based bots for incident investigation and production log analysis • Implement ClickHouse analytics pipelines and real-time anomaly detection • Develop constrained, repeatable diagnosis agents and internal tooling • Collaborate closely with TechOps, Connectivity, and Data teams

Role Description The Director RWD Data Engineering is a hands-on technical role that leads the end-to-end engineering vision for Lilly’s real-world data (RWD) infrastructure. This individual leads design and executes the scalable, cloud-native pipelines and data products that allow HEOR, SDIA, Statisticians, Medical, and Clinical teams to generate evidence faster, more reproducibly, and at greater scientific depth than is possible through traditional vendor engagements. This job involves a depth of understanding of the multi-modal RWD ecosystem across Lilly’s therapeutic areas to contextualize and drive RWD to the necessary end-user data products by leading the creation of sophisticated data engineering products, creating processes for automation of data ingestion and product creation, and leading special projects for Global Medical Affairs – Health Economics and Outcomes functions and the broader enterprise. Further, this position will be responsible for identifying and advocating standard processes across the data asset lifecycle, working closely with other data domain and analytics leaders. Collaborating closely with multi-functional teams, you will lead the technical implementation of data products, ensuring scalability, reliability, and performance. The ideal candidate possesses deep expertise in data engineering, strong problem-solving skills, and a passion for leveraging data to drive business outcomes. This position reports to HEOR Central and is embedded within the BIA organization and works in close partnership with HEOR, SDIA, Statisticians, Medical, and Clinical teams. Responsibilities - Lead the design, development, and implementation of cloud-native data products and high-throughput data pipelines that transform raw real-world data into scalable, reliable, analysis-ready assets supporting analytics, reporting, and evidence generation. - Lead the Analytic Data Products Strategy to deliver key data assets that enable streamlined, compliant execution and analytics. - Own the end-to-end lifecycle of RWD data products, from requirements gathering and prototyping through production deployment and optimization, ensuring scalability, reliability, performance, and reproducibility across cloud environments (e.g., Databricks, AWS S3, Azure Data Lake). - Build, optimize, and maintain ETL/ELT ingestion and transformation pipelines for large-scale, multi-modal RWD — including claims, complex EHR data, and other linked healthcare datasets — handling data volumes ranging from tens of millions to billions of records. - Implement and manage lakehouse-style data architectures (e.g., medallion bronze/silver/gold patterns) using Databricks and cloud object storage (AWS S3, ADLS) to produce versioned, partitioned, and audit-ready data assets. - Write and maintain reusable, version-controlled transformation logic incorporating healthcare coding and terminology standards (e.g., ICD-10/ICD-9, NDC, RxNorm, SNOMED, CPT/HCPCS, LOINC) to produce domain-level datasets such as demographics, diagnoses, treatments, procedures, encounters, and labs. - Optimize SQL and distributed processing workloads (e.g., Spark-based jobs) for performance across very large datasets, applying partitioning, indexing, predicate pushdown, denormalization, and other optimization strategies appropriate to analytical workloads. - Translate analytic, business, and research requirements into reproducible data extraction and transformation logic, supporting cohort construction, temporal logic, and consistent reuse of RWD across teams. - Apply deep understanding of healthcare data structures and standards when engineering data products, ensuring datasets are fit for purpose for downstream analytics and compliant with scientific, regulatory, and audit expectations. - Establish and implement standard engineering practices and methodology across the data asset lifecycle, including automated data ingestion, data quality checks, integrity testing, validation, monitoring, alerting, and documentation from source table to analysis-ready output. - Lead CI/CD pipeline setup, code review, and testing standards, ensuring all transformation code is version-controlled, tested, and deployable in a reproducible manner. - Collaborate closely with multi-functional partners — data scientists, statisticians, analytics leaders, and other technical teams — to understand business and technical requirements and develop documentation of RWD engineering standards, transformation templates, code list repositories, and pipeline performance guidelines. - Provide technical consultation to collaborators on appropriate use of data products and underlying RWD assets, including structural limitations of specific data sources, join strategies, and performance considerations; develop source-specific training materials for HEOR scientists, SDIA, and statisticians. - Develop and implement KPIs to measure system performance, efficiency and pull through to program impact. - Create an inclusive culture where producing and maintaining high-quality data is a core discipline. Qualifications - Bachelor’s degree in Computer Science, Engineering, Statistics, Information Technology, Bioinformatics or Technical Field. - Minimum of 5 years of hands-on data engineering experience. - Minimum of 5 years of applied expertise across Python, SQL, Java, Spring, Spring Boot, Prefect, and/or other business intelligence tools, ETL/ELT pipelines, and cloud platforms (AWS Glue/EMR, Snowflake, or Databricks), applied directly to real-world healthcare data at scale. - Minimum of 3 years of direct people management experience, including leading, coaching, and developing team members. Requirements - Master’s degree in Computer Science, Engineering, Statistics, Information Technology, Bioinformatics. - Minimum of 5 years of hands-on data engineering experience with a focus on healthcare or life sciences RWD Preferred. - Experience with distributed computing frameworks (Spark, Dask) for large-scale RWD processing. - Advanced SQL optimization skills for AWS Redshift and/or S3/Databricks-based architectures, including query tuning and workload management. - Deep understanding of healthcare coding standards (ICD-10, NDC, RxNorm, SNOMED CT, CPT, LOINC), real-world data structures, and major RWD vendors and platforms (Truveta, Optum, IQVIA, Komodo, HealthVerity). - Familiarity with DevOps and CI/CD practices relevant to data pipeline development and deployment. - Strong problem-solving skills, attention to detail, and ability to work effectively in matrixed, cross-functional teams with both technical and scientific partners. - Demonstrated ability to build production-grade ingestion pipelines for multi-terabyte, multi-modal datasets: claims, complex EHR. - Experience with OMOP CDM transformation, vocabulary management (Athena), and federated analytics networks (OHDSI, PCORnet, Sentinel). - Familiarity with bioinformatics workflow managers (Snakemake, Nextflow, WDL) and genomics cloud platforms (DNAnexus, Terra, AWS Genomics CLI). - Experience with data pipeline observability and quality tooling (dbt, Great Expectations, Monte Carlo). - Familiarity with FDA RWE Framework guidance, EMA RWD guidance, and audit-readiness requirements for observational studies. - Knowledge of Agile/Scrum methodologies and project management tools such as JIRA. - Knowledge and experience with –omics RWD: Genomics, Transcriptomics, Proteomics. Benefits - Comprehensive benefit program including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities). - Relocation assistance is available for qualified candidates.

Role Description - System Configuration - Follow-up Worklist – Per organization for worklist setup (e.g., reasons for follow-up, group creation, adding users, adding status outlines, adding follow-up letters). - Order Building – Per organization for non-medication ordering (e.g., building/creating orders, adding to applicable organizations, creating order sets/groups). - Lab Orders (In-House and Outside) – For any additional lab needed, build order for each organization. - Flowsheets – For any additional flowsheet modifications, update permissions and groupings. - Template Permissions – As requested, add permissions to templates. - Template Updates – Perform manual review of environments to note differences between the configured templates. Provide findings to the EHR Team. As requested, make updates to the template configuration. - ProDash Configuration – Per organization for ProDash setup (e.g., provider access). Development underway, more information pending. - Billing Template – Using provided outline, create billing template on each existing template and validate conditional logic. - System Support - Post system updates, perform system validation testing using provided script. Share findings with EHR Team. - Monitor end user support channels. Provide end user support based on provided script and common issue resolutions. Communicate with EHR Team when support is needed beyond script. - User Management - As received, complete updates to end user accounts (e.g., adding end date for users no longer needing access, updating locations, adding user roles, updating last name). Notify EHR Team if account is not located. - User Role Validation - Testing of user roles as new features or changes are implemented which could impact the user role. Report replaced findings. - Testing of user roles per new/copied environment to ensure accuracy. - Training Support - Format the Scribe documentation to become more human-readable. - Create training videos and other materials based on a provided script / guidance. - Using instructions, process EHR Training registration requests by verifying access setup in respective environment(s). Notify EHR Team of inaccuracies. - Medication Configuration - Drug Item Master – Select each site for each drug item. - Medical Formulary – Select each site and apply the individual drug items to the formulary. - Order Checks – Per provided instructions, create order checks for each site. - Order Management (Orderable Item, Order Group, Order Set) – Per provided instructions, complete medication building of the orderable item per site. For specific orderable items, add respective Regional Medical Director per site. Repeat process for order group and order set builds. - Implementation - Transfer applicable lots from regional/central pharmacy to each site ahead of their go-live. - Set initial inventory by lot at each site prior to the site go-live. - As requested, manually adjust inventory amounts from final current system count to future system. - Maintenance - As requested, complete new drug building at all applicable sites per each environment. - As requested, complete updates to drug items at all applicable sites per environment. Company Description