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Build and maintain AWS-based ETL pipelines (Glue/PySpark, Iceberg, Step Functions) and create Amazon QuickSight dashboards to deliver healthcare analytics for operational and strategic decisions.
Builds and maintains a scalable, event-driven data platform using Kafka, Java, and Spring for a banking-sector client.
Build and maintain an event-driven data platform using Kafka, Java/Spring Boot, and stream processing, while translating business needs into technical specs and integrating data flows.
Builds and maintains a real-time data pipeline for a Polish bank using Kafka, Spring Boot, MongoDB, GraphQL and Apache Iceberg, while analyzing business needs and mapping data flows.
DevOps engineer builds and maintains CI/CD pipelines, automates data pipelines, and manages hybrid DWH infrastructure using Kubernetes, Terraform, and Arenadata tools for a bank’s data warehouse.
Build and maintain a scalable event-driven data platform using Apache Kafka, Kafka Streams, and Spring Boot, integrating NoSQL databases and GraphQL APIs for a large Polish bank.
Build and maintain an event-driven data platform using Apache Kafka, Kafka Streams, and Spring Boot, integrating data sources and exposing GraphQL APIs backed by MongoDB.
Builds and maintains a real-time data pipeline using Kafka, Spring Boot, MongoDB, GraphQL, and Apache Iceberg, while analyzing business needs and mapping data flows.
Build and maintain Verkada’s enterprise data warehouse, automated pipelines, and analytics models to power company-wide reporting and AI-driven insights using Python, SQL, and cloud platforms like BigQuery or Snowflake.
Build and maintain real-time data pipelines using CDC, Kafka, Spark, and Iceberg to move and transform enterprise data across Bronze-Silver-Gold layers.
Build cloud-native, event-driven software for intelligent heating/cooling systems using Python, C#/.NET, PostgreSQL, Kafka, and Kubernetes in a climate-focused energy company.
Lead a team building and scaling a global KYC and risk-assessment data platform using Python/Java, Databricks, Spark, and cloud-native tools to deliver secure, AI-ready data pipelines.
Design and optimize cloud data pipelines and lake-house architectures for a global iGaming provider, migrating from on-prem to scalable cloud solutions while mentoring junior engineers.
Build and scale a cloud-native, multi-tenant data platform for the automotive industry, enabling real-time analytics and AI use cases across thousands of dealerships.
Build production-grade ML systems that detect retail crime patterns using computer vision, NLP, and graph analytics, deploying models on a cloud-native stack to power real-time alerts for global retailers.
Build and maintain AWS-based ETL pipelines that ingest Salesforce data into a Parquet-backed enterprise data lake, optimize Athena queries, and manage Redshift/Glue infrastructure using Terraform.
Designs and oversees TaskUs’s cloud-based data platform, choosing compute engines, open-table formats, and tiered storage to keep analytics fast, secure, and cost-efficient for high-concurrency users.
Build and optimize Amazon Athena’s serverless SQL query engine, solving distributed systems challenges to deliver fast, scalable analytics for millions of users.
Design and validate enterprise data platforms using open table formats (Iceberg), object storage, lakehouse architectures, governance, and streaming pipelines to support AI-ready analytics and compliance.
SAIC is seeking a highly experienced and motivated Senior Software Engineer to contribute to the integration of AI capabilities into expeditionary systems, including sensor kits, UxS, C2, and TAK. The successful…
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