3 Etl Fundamentals Jobs

NTT DATA is looking for a Databricks Engineer to join their team in Bangalore, Karnataka, India. As a Databricks Engineer, you will be responsible for various tasks related to data extraction, ETL pipeline modernization, job design, development, automation, metadata management, documentation, testing, collaboration, performance tuning, security, governance, and compliance. Your primary job duties will include extracting and analyzing data from SQL Server and Teradata sources, translating legacy SQL/DataStage transformations into Databricks-native code, building and orchestrating jobs within Databricks using tools like Databricks Workflows, Delta Lake, and Auto Loader, generating and maintaining data flow diagrams and job documentation, designing and executing unit tests and integration tests for data pipelines, optimizing data ingestion and transformation for performance and cost efficiency, ensuring compliance with data governance policies, and implementing access control via Unity Catalog. To be successful in this role, you must have a strong understanding of ETL/ELT principles and data pipelines, proficiency with Databricks platform and PySpark or Spark SQL, advanced SQL skills, familiarity with Teradata and SQL Server environments, ability to read and understand data models, schemas, and ERDs, basic proficiency with Git for code versioning, ability to write and validate unit/integration tests, strong communication skills, and an awareness of security and governance principles. NTT DATA is a global innovator of business and technology services, serving 75% of the Fortune Global 100. They are committed to helping clients innovate, optimize, and transform for long-term success. As a Global Top Employer, NTT DATA has diverse experts in more than 50 countries and a robust partner ecosystem. Their services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. NTT DATA is a leading provider of digital and AI infrastructure and is part of the NTT Group, investing in R&D to help organizations and society move confidently into the digital future. Visit us at us.nttdata.com.,

As a Data Specialist, you will be responsible for utilizing your expertise in ETL Fundamentals, SQL, BigQuery, Dataproc, Python, Data Catalog, Data Warehousing, and various other tools to contribute to the successful implementation of data projects. Your role will involve working with technologies such as Cloud Trace, Cloud Logging, Cloud Storage, and Datafusion to build and maintain a modern data platform. To excel in this position, you should possess a minimum of 5 years of experience in the data engineering field, with a focus on GCP cloud data implementation suite including BigQuery, Pub Sub, Data Flow/Apache Beam, Airflow/Composer, and Cloud Storage. Your strong understanding of very large-scale data architecture and hands-on experience in data warehouses, data lakes, and analytics platforms will be crucial for the success of our projects. Key Requirements: - Minimum 5 years of experience in data engineering - Hands-on experience in GCP cloud data implementation suite - Strong expertise in GBQ Query, Python, Apache Airflow, and SQL (BigQuery preferred) - Extensive hands-on experience with SQL and Python for working with data If you are passionate about data and have a proven track record of delivering results in a fast-paced environment, we invite you to apply for this exciting opportunity to be a part of our dynamic team.,

Mandatory keyskills : Athena, Step Functions, Spark - Pyspark, ETL Fundamentals, SQL (Basic + Advanced), Glue, Python, Lambda, Data Warehousing, EBS /EFS, AWS EC2, Lake Formation, Aurora, S3, Modern Data Platform Fundamentals, PLSQL, Cloud front We are looking for an experienced AWS Data Engineer to design, build, and manage robust, scalable, and high-performance data pipelines and data platforms on AWS. The ideal candidate will have a strong foundation in ETL fundamentals, data modeling, and modern data architecture, with hands-on expertise across a broad spectrum of AWS services including Athena, Glue, Step Functions, Lambda, S3, and Lake Formation. Key Responsibilities : Design and implement scalable ETL/ELT pipelines using AWS Glue, Spark (PySpark), and Step Functions. Work with structured and semi-structured data using Athena, S3, and Lake Formation to enable efficient querying and access control. Develop and deploy serverless data processing solutions using AWS Lambda and integrate them into pipeline orchestration. Perform advanced SQL and PL/SQL development for data transformation, analysis, and performance tuning. Build data lakes and data warehouses using S3, Aurora, and Athena. Implement data governance, security, and access control strategies using AWS tools including Lake Formation, CloudFront, EBS/EFS, and IAM. Develop and maintain metadata, lineage, and data cataloging capabilities. Participate in data modeling exercises for both OLTP and OLAP environments. Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights. Monitor, debug, and optimize data pipelines for reliability and performance. Required Skills & Experience: Strong experience with AWS data services: Glue, Athena, Step Functions, Lambda, Lake Formation, S3, EC2, Aurora, EBS/EFS, CloudFront. Proficient in PySpark, Python, SQL (basic and advanced), and PL/SQL. Solid understanding of ETL/ELT processes and data warehousing concepts. Familiarity with modern data platform fundamentals and distributed data processing. Experience in data modeling (conceptual, logical, physical) for analytical and operational use cases. Experience with orchestration and workflow management tools within AWS. Strong debugging and performance tuning skills across the data stack.