Top Data Management Jobs

Lead development, deployment, and optimization of cloud data platforms and real-time pipelines. Manage cross-functional on-site and offshore teams, ensure production stability, troubleshoot issues, optimize AWS and data warehouse cost/performance, implement CI/CD for pipelines, and integrate AI-driven ops for anomaly detection and predictive data quality.

Lead a product analytics team to measure and improve product and platform performance. Mine and analyze large datasets, build and validate models, implement reporting and BI improvements, consult on data/storage system design, run strategic tests, mentor junior analysts, and collaborate cross-functionally to drive data-informed product decisions.

Lead and scale a data engineering team to build and maintain BigQuery-based ELT pipelines and Medallion architecture. Provide technical direction, hands-on engineering (dbt, Python, Fivetran), enforce governance, data quality, observability, CI/CD and IaC standards, and partner with platform and business domains to deliver a reliable data platform.

Lead a data engineering team building pipelines, transformations, and analytics infrastructure in Azure/AWS/Snowflake. Champion spec-driven, AI-assisted development, ensure secure scalable systems, govern AI-generated code, and partner with product and platform teams.

Serve as a second-line data risk advisor by validating enterprise analytical tools, conducting risk and gap assessments, influencing stakeholders, designing controls, leading validation projects, mentoring staff, and ensuring data management practices meet regulatory and enterprise risk standards.

Design, build, and test SAP MDM repositories and logical data models. Configure MDM clients (Console, Data Manager, Import Manager, Syndication Manager), create import/syndication maps, workflows, web services, DB views, and INI files. Perform repository operations with CLIX, prepare unit tests, validate integrations with upstream/downstream systems, and coordinate with data providers and consumers.

Design, build and maintain SAP MDM repositories and logical data models. Create functional and technical specs, configure MDM clients (console, data/import/syndication managers), web services, CLIX server ops, import/syndication maps, workflows, matching rules, DB views and INI files. Perform unit testing, validation and liaison with data providers.

Implement and configure SAP MDM repositories and clients; design functional/technical specs, import/syndication maps, workflows, web services, CLIX operations, DB views, and test interfaces between MDM and upstream/downstream systems.

Design, build, and validate SAP MDM repositories and logical data models. Configure MDM clients (console, data manager, import/syndication managers), create import/syndication maps, workflows, matching rules, and DB views; perform CLIX and server-level operations, INI configuration, and interface testing. Liaise with data providers, subscribers, and downstream systems and lead the team.

Design, build, and validate SAP MDM repositories and logical data models; create import and syndication maps; configure MDM clients, web services, CLIX operations, DB views and INI files; design workflows, matching rules, validations, and unit tests; liaise with data providers and lead/Mentor team activities.

Implement and configure SAP MDM solutions: create repositories and import/syndication maps, design functional/technical specs, configure MDM clients and web services, build workflows, matching rules, validations, and data manager operations to support master data processes.

Implement and maintain SAP MDM repositories and mappings. Design functional/technical specs, configure MDM clients (Console, Data Manager, Import/Syndication Manager), create import/syndication maps, web services, DB views and INI configurations. Develop workflows, matching rules, validations, CLIX server ops, unit tests, and test interfaces with upstream/downstream systems. Collaborate with data providers and cross-functional teams.

Implement and maintain SAP MDM repositories and logical data models; design functional/technical specs; build import/syndication maps; configure MDM clients and web services; develop workflows, matching rules, validations, and DB views; use CLIX for server/repository operations; test/unit-test repositories and interfaces; collaborate with data providers and consumers across business units.

Design, build, and validate SAP MDM repositories and logical data models. Create functional/technical specs, import and syndication maps, configure MDM clients and web services, perform repository/CLIX operations, implement workflows, matching rules, validations, and DB views, prepare unit tests, and collaborate with data providers and business stakeholders while leading and motivating the team.

Lead design and implementation of SAP MDM repositories and data models; configure MDM clients, import/syndication maps, workflows, web services and CLIX operations; develop and test integrations with upstream/downstream systems; produce technical specifications and unit tests; coordinate with data providers and stakeholders.

Design, build, and test SAP MDM repositories and logical data models. Configure MDM clients (Console, Data Manager, Import/Syndication Managers), create import/syndication maps, web services, workflows, matching rules, and DB views. Perform CLIX and server/repository operations, configure INI files, prepare unit tests, validate repositories, and coordinate with data providers and consumers.

Design, build, test and maintain SAP MDM repositories, import/syndication maps, workflows and web services. Perform data modeling, repository and server operations (CLIX), unit testing, and validate interfaces with upstream/downstream systems while coordinating with data providers and stakeholders.

Design, build, and test SAP MDM repositories and logical data models; configure MDM thick clients, import/syndication maps, web services, INI files and DB views; develop workflows, matching rules and validations; perform CLIX server/repository operations; create unit tests and validate interfaces with upstream/downstream systems; liaise with data providers and stakeholders.

Implement and configure SAP MDM repositories, design functional/technical specs, build import/syndication maps and web services, manage MDM clients and CLIX operations, design workflows and matching rules, create DB views and INI configurations, and validate/test MDM solutions while collaborating with stakeholders.

Implement and maintain SAP MDM repositories and logical data models; produce functional and technical design specs; configure MDM clients, import/syndication maps, web services and INI files; perform CLIX and DB view operations; design workflows, matching rules and validations; prepare unit tests; validate repositories; test interfaces with upstream/downstream systems; liaise with data providers and lead the team.

Lead and grow a data engineering team, define data platform architecture and reliability (warehouse, ingestion, transformations, orchestration), set engineering standards, partner cross-functionally to support analytics and ML, and translate technical decisions for executive stakeholders.

The Senior Manager will lead cross-functional analytics projects, validate analytical tools, and mentor junior staff while driving data-based business strategies.

The Manager of Data Integrations will oversee data reconciliations for SAP SuccessFactors, governance, compliance, and integration across various systems for sales compensation programs.

Lead and grow a Data Governance team to build and run governance programs: metadata standards, taxonomy, glossary migration, data catalog ownership (Atlan), asset certification, data quality observability, and stakeholder adoption. Act as subject-matter expert, enforce certification standards, arbitrate definitions, and apply AI tooling to scale governance work.

Lead a small data engineering team and own market data platforms from ingestion through delivery. Build and maintain KDB+/Q time-series systems, ensure data correctness, low-latency decoding, replay/recovery, and reliable distribution to downstream consumers. Write production code, review designs, improve observability, and prepare the platform for AI-driven consumers.