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ИТ B2C — самая крупная экосистема в Сбере. Нас более 8000 человек в 18 городах России. Мы занимаемся разработкой и развитием розничных решений, помогая сделать сервисы Банка доступнее, безопаснее и удобнее. Ждем именно…
Lead Data Engineer owning the architecture, scalability, and technical direction of Amtech's Cloud Data Platform—designing data warehouses, ETL/ELT pipelines, tenant data stores, and feature stores that power analytics and AI agent initiatives using cloud platforms (AWS/Azure/GCP), big data frameworks (Spark, Kafka), and warehousing tools (Snowflake/Redshift/BigQuery).
Senior Full Stack .NET Software Engineer developing a new cross-platform (Windows/Linux, on-prem and cloud) software platform in C#, TypeScript, and React for nuclear medicine hospital systems and the radiopharmaceutical industry.
Design, build and maintain scalable backend services for a GRC SaaS platform focused on AI, privacy and security governance, using Node.js, TypeScript and Java in Rotterdam.
Data Engineer (Azure Databricks Developer) with 7+ years experience designing and maintaining scalable data pipelines using Azure Databricks, developing ETL/ELT processes, building Spark-based applications, and ensuring data security and governance.
Azure Data Engineer building and supporting data pipelines, ETL processes, and large SQL data marts using Azure Data Factory, Databricks, Synapse, and Python.
Senior Data Engineer designing and developing large-scale data processing and persistence software using big data platforms like AWS, Azure, GCP, and Databricks, primarily with Java, Scala, or Python.
A Databricks Data Engineer role involving hands-on data engineering with Apache Spark, Databricks, Python/Scala, ETL pipelines, data warehousing, and cloud services (AWS/Azure) for large datasets.
AWS Data Engineer designing data strategies, building big data solutions on AWS/Spark/Hadoop, programming in Scala/Python/Java/SQL, and tuning Spark for billion-record processing.
GCP Data Engineer at TCS Chennai responsible for developing, deploying, monitoring, and optimizing batch ETL workflows using Scala, PySpark, Airflow, BigQuery, and Dataproc on GCP with Medallion architecture experience.
Senior Data Engineer building and optimizing batch and streaming ETL workflows on GCP using Scala, Spark, Kafka, Airflow, and Dataproc within TCS's Data & Analytics unit.
Freelance Senior Data Engineer designing scalable AWS data pipelines, ETL processes, and data warehouses using AWS Glue, Snowflake, Python/PySpark, and Terraform.
Lead Data Engineer at IndusInd Bank in Mumbai, architecting and building a cloud-native Azure Databricks data platform with PySpark, leading a team of data engineers and analysts to deliver scalable lakehouse architectures and BI solutions.
Senior Data Engineer lead building complex ETL/ELT solutions on Azure Data Lake, Databricks, and ADF using SQL, PySpark/Scala, with Kafka-based real-time and batch ingestion at scale.
Design and develop real-time data pipelines and scalable data processing solutions on AWS using Kafka, Spark, and AWS Kinesis.
The Senior Data Solutions and Cloud Architect/Engineer will design and manage scalable cloud-based data environments on Azure to support advanced analytics and business decision-making. The role involves leading technical teams, building data pipelines, and ensuring compliance with security and GxP standards within a MedTech environment.
Design, build, and maintain the analytics data layer—pipelines (Airflow), warehouse (BigQuery), and ETL—on GCP, applying software engineering best practices to deliver BI solutions.
Tech Lead / SDE IV owning batch and real-time data pipelines for a programmatic advertising DSP, processing billions of bid-stream events daily with Kafka, Flink, StarRocks, and Python/Java/Scala, while also architecting backend microservices and mentoring engineers.
Senior Databricks Engineer automating platform operations, CI/CD pipelines, and multi-environment deployments using Databricks, PySpark, SparkSQL, and Azure cloud services.
Senior Data Engineer designing and building scalable data pipelines with Apache Spark, Scala, and Java, plus microservices and Redis caching in distributed environments.
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