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Thermo Fisher Scientific is seeking a Lead Database Engineer to design, build, and optimize AWS-based data lake and data warehouse platforms. You will lead database architecture, performance tuning, data quality,…
Owns and scales ETL pipelines for healthcare data using PySpark, Python, SQL, and AWS, while ensuring PHI/PII security and governance in a regulated environment.
Lead Data Engineer responsible for designing, building, and maintaining scalable healthcare data pipelines in AWS, handling PHI/PII securely, and integrating AI/ML for mapping and data quality while owning the full pipeline lifecycle from development to production.
Build and maintain ETL/ELT pipelines and PySpark jobs to feed AI and analytics platforms, ensuring reliable data flow for enterprise-scale products.
Builds and maintains data pipelines, ETL jobs, and dashboards for a government authority using Python, PySpark, Cloudera, and Tableau.
Build and maintain high-performance Databricks pipelines in Python and SQL to power AI and analytics for enterprise clients in finance, healthcare, and tech.
Lead Data Engineer designs and builds modern data platforms (Databricks, Azure Synapse) and pipelines, mentors teams, and shapes Forte’s Data & AI strategy while collaborating with clients and stakeholders.
Design, build, and maintain scalable data pipelines and analytics solutions using AWS, Python, SQL, PySpark, and Apache Airflow for a hybrid role in Madrid.
Build and maintain a centralised Microsoft Fabric data warehouse using PySpark and SQL, applying medallion architecture to turn raw source data into trusted, analytics-ready products for CommBank.
Designs and builds scalable Azure data pipelines and platforms to ingest, transform, and deliver clean data for analytics and reporting in a sustainability-focused chemicals company.
Build and maintain cloud-based data pipelines and warehouses in Azure to power automotive industry analytics, using Synapse, Data Factory, PySpark, and SQL.
Build and migrate data pipelines from Teradata to AWS Lakehouse using Databricks, dbt, Airflow, and Iceberg for a regulated financial services client.
Designs and builds scalable AWS data pipelines using Python, PySpark, Airflow MWAA, and Redshift to power analytics and data warehousing.
Build and optimize scalable data pipelines in Microsoft Fabric using PySpark and SQL, transforming raw data into analytics-ready layers for CommBank’s centralized warehouse.
Designs and builds scalable Azure Databricks pipelines using PySpark and Delta Lake to implement ETL/ELT frameworks across a lakehouse architecture.
Builds and optimizes scalable data pipelines on Azure using Databricks, PySpark, Delta Lake, and related services for ETL/ELT and streaming workloads.
Builds and maintains the data pipelines and Lakehouse/Warehouse models in Microsoft Fabric for a mobility group’s BI modernization, using PySpark, Data Factory, and Medallion architecture.
Senior Data Engineer builds and maintains scalable batch/streaming pipelines (PySpark, SQL) for EY GDS Spain, supporting clients’ digital transformation with distributed data processing and ETL/ELT workflows.
Build and maintain scalable data platforms on Databricks and cloud (Azure/AWS/GCP) to enable data-driven decisions for clients and partners.
Build and maintain scalable data platforms on Databricks and cloud providers (Azure/GCP/AWS) to enable data-driven decision-making for EY clients.
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