Top Data & Analytics Jobs

Design, build, and operate Azure/Databricks Lakehouse solutions including batch and streaming ingestion, storage and dimensional modeling, data transformation and quality, Power BI semantic layers and reporting, observability and security, and cost optimization across data pipelines.

Design, build, and operate Azure + Databricks Lakehouse pipelines (batch & streaming), ensure data quality/observability, model curated datasets for Power BI, enforce security/compliance, and drive cost optimization across data lifecycle.

Design, build, and operate Azure/Databricks lakehouse pipelines (batch and streaming) with governance, data quality, observability, and cost controls. Model curated datasets and semantic layers in Power BI, manage PostgreSQL replication/CDC to lakehouse/Synapse, enforce security/compliance, and collaborate with product owners and data stewards to certify enterprise datasets.

Design and operate Azure + Databricks lakehouse architectures; build batch and streaming ingestion pipelines with CI/CD, data quality, CDC, and observability; model curated datasets and semantic layers for Power BI; enforce security, compliance, and cost-optimization; collaborate with product owners and data stewards to certify enterprise datasets.

Design and operate an Azure + Databricks lakehouse; build batch and streaming ingestion pipelines with CDC, automated data quality, CI/CD and observability; model curated datasets and semantic layers for Power BI; enforce security/compliance controls and cost optimization; collaborate with product owners and data stewards.

Design, operate, and govern an Azure + Databricks lakehouse across ingestion, storage, transformation, and serving. Build batch and streaming pipelines with CI/CD, automated data quality, observability, and security controls. Model curated datasets and semantic layers for Power BI, manage PostgreSQL replication and CDC, optimize costs, and collaborate with product owners and data stewards to certify enterprise metrics.

Design, build, and operate scalable cloud and on-prem data systems and pipelines using Azure, Databricks, Spark, Kafka, and Snowflake. Collaborate with architects, DevOps, and product teams to convert .NET ETL to cloud, automate infrastructure and CI/CD, ensure security and compliance, and deliver high-quality, production-ready data services.

Design, build, and maintain end-to-end data pipelines and integrations using Azure Data Factory, DBT, and Snowflake. Optimize SQL and Snowflake performance, support batch ingestion and API-based integrations, mentor engineers, produce technical documentation and runbooks, and ensure data quality, monitoring, and secure compliant data transfers.

Design, build, and operate Azure + Databricks lakehouse architectures. Implement batch and streaming ingestion, CDC, data modeling for BI, automated quality checks, CI/CD, observability, security controls, cost optimization, and Power BI semantic layers with enterprise governance and certified datasets.

Perform data-driven analysis, validation, and end-to-end UAT across Risk & Quality systems. Design and execute SQL-based backend validations, reconcile upstream/downstream data, create production-like test datasets, and perform root cause analysis for data defects. Develop and maintain UI, database, and API test automation using Java, Selenium, TestNG, and Cucumber, and collaborate in Agile teams to ensure business-aligned releases.