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GCP Data Engineer role focused on building and maintaining data pipeline architecture, data warehouse modernization, and cloud-based data lakes using Google Cloud Platform big data technologies and PySpark.
Lead Data Engineer building data pipelines for analytics and data science use cases on Big Data platforms, primarily using Spark, Scala, Hadoop, and Hive.
Senior Data Engineer building secure, automated, scalable GCP data pipelines using Python, Apache Airflow, Apache Druid, and Spark for a global ad-tech DSP platform.
Lead/Senior Data Engineer designing and delivering scalable data pipelines and platforms using Python, Scala, Spark, and SQL, while mentoring a team and collaborating cross-functionally.
Senior Data Engineer building scalable data platforms on Azure using Scala and Spark, handling data ingestion, transformation, and analytics enablement for a digital transformation consultancy.
Build and maintain scalable data pipelines using Spark, Scala, Airflow, and Azure Databricks in a hybrid role based in Bengaluru. Work with modern data lakehouse technologies, containerization, and CI/CD practices.
Senior Data Engineer building and operating production-grade data pipelines on AWS (S3, Glue, EMR, Redshift, Lambda) using Python and SQL, with Airflow, Delta Lake, and streaming tools, for a political/policy research analytics firm in Bangalore (hybrid).
Design, develop, and optimize large-scale data processing solutions and high-performance data pipelines using Spark, Scala, and the Hadoop ecosystem for distributed analytics platforms.
Big Data Engineer designing, developing, and optimizing scalable data pipelines using PySpark, Hadoop ecosystem tools (HDFS, Hive, Sqoop), SQL/HiveQL, and workflow orchestration via Airflow or Oozie.
Mid-Level Big Data Engineer with 4-6 years of experience building and supporting large-scale Big Data applications and cloud-based data pipelines using Python, AWS EMR, Spark, SQL, and AWS cloud services with focus on EMR performance tuning and cost optimization.
An AWS Data Engineer designing and implementing big data solutions, tuning Spark for high-volume data processing, and troubleshooting performance issues.
Data Engineer designing and building data pipelines, ETL/ELT processes, and data models using Azure Data Factory, SQL, and big data technologies to support analytics and business insights.
Build and maintain data pipelines, ETL processes, and RESTful APIs using cloud platforms (GCP/AWS/Azure) and big-data tools (Spark, SQL) to support AI-driven servicing platforms at American Express.
Position Summary Hive Group, a HUBZone-certified SDVOSB and multiple award-winning organization, delivers innovative solutions for complex, mission-critical federal programs. We are seeking a highly skilled elite…
Business Unit/Role Specific Information The Credit and Fraud Risk (CFR) team at American Express employs 3,500 global professionals focused on managing credit, fraud, and banking risk, optimizing risk trade-offs while…
This Data Engineer role involves leading a team to build and maintain robust data pipelines, migrate legacy systems to Snowflake, and optimize cloud infrastructure using AWS Glue, Python, and Spark. The position focuses on BAU operations, production support, and collaborating with stakeholders to ensure data quality and scalability.
The Senior Data Engineer will modernize and optimize NBME's data platform by building scalable data pipelines, data lakes, and AI/ML-ready data solutions on AWS. This role involves collaborating with cross-functional teams to support analytics and AI initiatives while promoting AI-assisted engineering best practices.
The Assistant Manager - Business Analyst acts as a liaison between business stakeholders and technical teams to define requirements and functional solutions for US healthcare payer projects. The role involves managing backlogs in Jira, creating documentation, and leveraging data analytics to optimize healthcare business processes.
Must-Have: ● 4+ years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills. ● SQL, Pyspark, Python with Banking Domain knowledge - Credit & Lending. Working…
Обязанности: SberData - департамент по управлению данными всего Сбербанка. SberData строит централизованное хранилище данных, объем которого уже превышает 100 ПБ. Это продуктово-ориентированная инженерная команда с…
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