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Data Engineer
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Data Engineer
Accenture- Posted 13 hours ago
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Job Description
Project Role : Data Engineer
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Snowflake Data Warehouse
Good to have skills : NA
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand their data needs and provide effective solutions, ensuring that the data infrastructure is robust and scalable to meet the demands of the organization.
Roles & Responsibilities:
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Snowflake Data Warehouse
Good to have skills : NA
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand their data needs and provide effective solutions, ensuring that the data infrastructure is robust and scalable to meet the demands of the organization.
Roles & Responsibilities:
- Expected to be an SME.
- Collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Mentor junior team members to enhance their skills and knowledge in data engineering.
- Continuously evaluate and improve data processes to enhance efficiency and effectiveness.
- Must To Have Skills: Proficiency in Snowflake Data Warehouse.
- Experience with data modeling and database design.
- Strong understanding of ETL processes and data integration techniques.
- Familiarity with cloud platforms and services related to data storage and processing.
- Knowledge of data governance and data quality best practices.
- The candidate should have minimum 7.5 years of experience in Snowflake Data Warehouse.
- This position is based at our Mumbai office.
- A 15 years full time education is required.
More Info
Key Skills
Snowflake Data Warehouse
ETL processes
data integration techniques
data quality best practices
cloud platforms and services
About Company
Skills:
Data Modeling, Sql, data pipeline development, Snowflake Data Warehouse, ETL processes, data quality frameworks, database design principles, data querying techniques, data governance practices
Skills:
snowflake , Metadata Management, Sql, Apache Airflow, Docker, Kubernetes, Python, ETL ELT frameworks, AI-native development tools, SDK and API-based development, cloud-native technologies, streaming technologies, Agentic AI, dbt, cloud data warehouse platforms
Skills:
Aws Services, Data Modeling, Amazon S3, Pyspark, AWS Glue, Lambda, Data Migration, Terraform, Python, Spark SQL, Apache Spark, Emr, Shell Scripting, Redshift, Sql, Git, Cloudwatch, Iam, Data Warehousing, Etl, CI CD Pipelines, Infrastructure as Code, Batch Processing, Step Functions, Data Lakes, ELT Development, Athena
Skills:
data engineering , Power Bi, Power Automate, Data Warehousing, Data Integration, Sql, Power Apps, data modeling best practices, API data integration, error logging, error handling
Skills:
Github, Performance Tuning, Data Factory, Pyspark, Azure DevOps, Power Bi, Apache Spark, Sql, Metadata Management, Data Warehousing, Databricks, Data Pipelines, Warehouse, Microsoft Fabric components, Governance practices, Automated testing and validation frameworks, Data quality reconciliation, Databricks Workflows, Semantic Models, Lakehouse Architectures, Data Integration Frameworks, ETL ELT Solutions, Lakehouse, CI CD pipelines, Delta Lake, Microsoft Fabric, Automation and Orchestration