Top Tech Jobs & Startup Jobs

Designs, builds, and maintains scalable batch and streaming data pipelines, lakehouse architectures, transformation layers, and data models. Develops PySpark and SQL solutions, integrates diverse data sources, implements data quality monitoring, and manages infrastructure as code. The role also troubleshoots performance and pipeline incidents, participates in code reviews, collaborates with architects, and mentors junior and mid-level data engineers.

Build and maintain CI/CD pipelines, infrastructure automation, Kubernetes-based data platform environments, and observability tooling. Manage Terraform and Helm deployments, cloud cost optimization, provisioning, policy enforcement, incident response, capacity planning, and operational documentation. Collaborate with data engineering and security teams to improve reliability, scalability, compliance, and engineering productivity across enterprise lakehouse platforms.

Deploys, operates, and extends LinkedIn DataHub across cloud and on-premises environments. Integrates lakehouse and BI platforms, manages metadata ingestion, builds lineage graphs, implements classification and stewardship workflows, and develops custom plugins and APIs. The role also monitors platform performance, translates governance policies into controls, and trains data stewards and consumers.

Design and implement enterprise data quality frameworks for lakehouse platforms. Build automated validation tests, dashboards, anomaly detection, observability solutions, and CI/CD quality checks. Manage data quality SLAs, profile new sources, resolve incidents, collaborate with governance and source owners, and educate engineering and product teams on quality standards.

Designs, builds, and maintains enterprise lakehouse data pipelines, transformation layers, and data models. Develops scalable batch and streaming solutions using Spark, Kafka, and Flink; implements medallion architecture, data quality monitoring, and infrastructure as code. Troubleshoots performance and data incidents, participates in code reviews, collaborates on data modeling, and mentors junior and mid-level engineers.

Owns the lifecycle, roadmap, and delivery of data products on a lakehouse platform. Defines requirements, schemas, SLAs, access controls, documentation, and KPIs; manages catalogs and metadata; leads sprint planning, backlog grooming, capacity, and releases; and coordinates with data engineering, governance, security, and compliance teams to ensure quality, adoption, discoverability, and business value.

Leads information security, data privacy, and regulatory compliance for an enterprise data lakehouse platform. Defines access controls, encryption, classification, and security frameworks; manages risk assessments, threat modeling, vulnerability testing, audits, incident response, and remediation. Partners with engineering teams to embed controls into CI/CD and data workflows, maintains compliance evidence, and trains teams on secure data handling.

Lead the strategy, roadmap, development, and adoption of Dynata’s enterprise data platform and lakehouse ecosystem. Prioritize platform-enabled use cases, align investments with business value, oversee implementation with engineering and data teams, establish governance and success metrics, and drive stakeholder adoption. Initially hands-on, the role will later build and scale a product management organization while partnering with executives, vendors, and cross-functional teams.

Designs and delivers practical AI learning programs, workshops, office hours, job aids, prompt guides, and role-based enablement resources. Supports adoption of Claude, Microsoft Copilot, Perplexity, and other approved tools by teaching prompt writing, output review, responsible use, and human oversight. Partners with HR, Technology, Legal, Information Security, Communications, and business stakeholders to coordinate programs, facilitate sessions, measure participation and adoption, and continuously improve learning content.

Manage employee engagement, talent management, and performance reviews. Lead HR systems implementation and process improvements. Ensure labor law and benefits compliance. Provide administrative support to HR and HR ops teams.