• Design, implement, and maintain data pipelines and ETL processes supporting ingestion, transformation, and validation of mission data • Develop and optimize data models and schemas across relational and non-relational databases to support system integrations and analytics • Collaborate with system architects, integration developers, and data analysts to ensure data consistency, security, and integrity across cloud environments • Implement data migration and synchronization between legacy systems, applications, and modern cloud platforms • Utilize AWS services (Glue, Lambda, S3, RDS, Redshift, Kinesis) to build and sustain scalable and fault-tolerant data infrastructure • Support data validation and reconciliation, performing quality checks and developing reports to ensure accuracy • Integrate data from APIs, streaming sources, and file-based systems into centralized repositories or data lakes • Automate data workflows using infrastructure-as-code and CI/CD principles to ensure repeatability and efficiency • Monitor and troubleshoot data pipeline performance, ensuring adherence to SLAs and operational reliability • Implement data encryption, masking, and access controls in compliance with DoD cybersecurity policies and RMF requirements • Support development of dashboards and analytics products, enabling data-driven insights for mission stakeholders • Maintain documentation and metadata repositories, including data dictionaries, lineage, and technical specifications • Participate in Agile sprints, contributing to backlog refinement, testing, and cross-functional collaboration

• Design, build, and maintain **schemas and data models** • Optimize table layout, partitioning, indexing, and compression for high-volume data • Ensure fast, efficient querying for logs, requests, metrics, and performance traces • Maintain ingestion pipelines for billions of records • Build robust pipelines for: - API logs - Model inference logs - Error events - Usage & integration events - GPU & system metrics • Implement ETL/ELT workflows to transform raw data into analytics-ready structures • Ensure quality, reliability, and real-time availability of data sources • Build tooling to support large-scale **log analysis** • Enable deep investigation into latency, throughput, errors, and bottlenecks • Provide the raw data foundation for E2E inference-time monitoring • Help debug production issues using logs and traces • Work closely with DevOps, ML, and backend engineering • Integrate pipelines with monitoring tools (Prometheus, Grafana, Datadog, OpenTelemetry) • Automate ingestion and cleanup tasks • Build internal libraries or utilities to support monitoring and debugging workflows • Provide clean data interfaces for the Data Expert (dashboards, monitoring, analytics) • Support engineering teams by exposing the right logs and metrics • Contribute to debugging, RCA (root cause analysis), and performance optimization initiatives

Title: CDTL Location: Bangalore Karnātaka India Full time Remote Join Us as a Clinical Data Team Lead – Make an Impact at the Forefront of Innovation We have successfully supported the top 50 pharmaceutical companies and more than 750 biotechs, spanning 2,700 clinical trials across 100+ countries in the last 5 years. As part of our expert team, you’ll have the opportunity to ensure operational excellence that makes a real difference in organizational performance. As a Clinical Data Team Lead, you will act as the lead data manager for one or more projects or provide support to the lead data manager. You may lead all data management activities for individual, limited volume/complexity studies with support from senior team members. Additionally, you will act as an interdepartmental and client liaison for all data management study activities. What You’ll Do: • Applies relevant components of the project protocol to daily tasks and directs others on how to apply to their daily tasks. • Acts as a liaison to the Project Lead and/or client as required and communicates with management regarding all data management (DM) activities within their studies. • Develops and maintains data management project documentation files; performs independent reviews of data management deliverables following documented CDM guidelines. • Develops and delivers study specific training for DM project staff. • Produces project-specific status reports for management, Project Lead and/or clients on a regular basis. Monitors study metrics. • May participate in business development activities by assisting with bid preparation and/or representing data management at bid defense meetings, where required. • Assists with project forecasting of hours and identification of resource requirements and identifies potential out of scope activities to Project Lead and management and assists with the Contract Modification process. • Mentors junior level staff on all associated tasks within a study. • Assists with the administrative and financial management of allocated projects. Performs all assigned data management activities independently and efficiently, with attention to quality. Education and Experience Requirements: • Bachelor's degree or equivalent and relevant formal academic / vocational qualification • Previous experience that provides the knowledge, skills, and abilities to perform the job (comparable to 2+ years). In some cases an equivalency, consisting of a combination of appropriate education, training and/or directly related experience, will be considered sufficient for an individual to meet the requirements of the role. Knowledge, Skills and Abilities: • Ability to effectively apply knowledge and skills in a highly organized fashion while adhering to regulatory guidelines, SOPs and client expectations • Ability to use interactive computer programs • Good written/ verbal communication skills with a strong command of English language and grammar; good organizational, analytical/problem solving skills and attention to detail • Ability to work productively with minimal supervision • Ability to maintain a high degree of confidentiality with clinical data and client's proprietary data • Strong customer focus and excellent interpersonal skills • Proven flexibility and adaptability • Ability to work in a team environment and independently as needed • Ability to train and direct study team • Ability to set and meet timelines or be able to recognize and schedule changes in response to project demands

• Design and build ETL pipelines that ingest, validate, and standardize data from multiple sources with high accuracy and performance • Develop matching logic and fuzzy matching algorithms using tools like rapidfuzz to identify and reconcile data discrepancies across datasets • Create automated report generation systems that produce Excel and PDF outputs with complex formatting, formulas, and dynamic content • Implement data transformation workflows including date normalization, field mapping, and scenario classification based on business rules • Write comprehensive unit tests using pytest and maintain code quality through version control (Git) and code review practices • Translate business requirements into technical specifications, documenting matching rules, reconciliation scenarios, and data workflows directly from stakeholder discussions • Optimize database queries and data operations using relational databases (PostgreSQL, MySQL) and SQLAlchemy ORM for efficient data access • Collaborate with cross-functional teams to troubleshoot data issues, validate outputs, and continuously improve pipeline reliability and performance