Search by job, company or skills

Data Engineer

Data Engineer

Accenture
5-7 Years
Not Disclosed
Early Applicant
  • Posted a day ago
  • Be among the first 10 applicants

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 : Amazon Redshift, AWS S3 (Simple Storage Service), AWS DynamoDB

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary

As a Data Engineer, a typical day involves designing, developing, and maintaining comprehensive data solutions that support the generation, collection, and processing of data. This role requires creating efficient data pipelines and ensuring the integrity and quality of data throughout its lifecycle. The position also involves implementing processes to extract, transform, and load data, facilitating seamless migration and deployment across various systems. Collaboration with different teams to optimize data workflows and troubleshoot any issues that arise is an integral part of the daily routine, ensuring that data solutions meet organizational needs effectively and reliably.

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.
  • Lead the design and implementation of scalable data architectures to support business requirements.
  • Mentor junior team members to enhance their technical skills and understanding of data engineering best practices.
  • Continuously evaluate and improve existing data processes to increase efficiency and reliability.

Professional & Technical Skills

  • Must To Have Skills: Proficiency in Snowflake Data Warehouse.
  • Good To Have Skills: Experience with AWS S3 (Simple Storage Service), AWS DynamoDB, Amazon Redshift.
  • Strong knowledge of data pipeline development and orchestration techniques.
  • Experience with data integration and ETL tools to manage complex data workflows.
  • Ability to optimize data storage and retrieval for performance and cost efficiency.
  • Familiarity with cloud-based data storage and processing environments.

Additional Information

  • The candidate should have minimum 5 years of experience in Snowflake Data Warehouse.
  • This position is based at our Bengaluru office.
  • A 15 years full time education is required.

Exception - New Project

More Info

Job Type:
Industry:
Employment Type:

Key Skills

data pipeline development

Snowflake Data Warehouse

cloud-based data storage and processing

orchestration techniques

AWS S3 Simple Storage Service

AWS DynamoDB

About Company

Similar Jobs

3-5 yrs
Gurugram, Gurugram, India
Skills:
Data Governance, Data Warehousing Concepts, data storage solutions, ETL processes, data integration techniques, data quality best practices, Microsoft Azure Databricks
5-7 yrs
Gurugram, Gurugram, India
Skills:
Amazon Web Services (AWS), Java, Hadoop, Scala, Nodejs, Emr, Data Modeling, Sql, Hive, Spark, Python, Agentic AI tools, AI code generation tools, ETL pipelines
4-7 yrs
Gurugram, Gurugram, India
Skills:
Azure Data Bricks, Pyspark, Performance Tuning, Data Warehousing, Data Modeling, Sql, ELT, Azure Data Factory, Azure Data Lake, Databricks, automation, Python, Etl, Azure Cloud technologies, pipeline development, Delta Live Tables, Unity Catalog, Delta Lake, Autoloader
4-8 yrs
Gurugram, India, Gurugram
Skills:
snowflake , Bi Tools, Data Governance, Nosql, Amazon Redshift, Apache Hive, HDFS, Data quality management frameworks, Warehouse SQL
5-7 yrs
Gurugram, Gurugram, India
Skills:
Amazon Web Services (AWS), Java, Hadoop, Scala, Nodejs, Emr, Data Modeling, Sql, Hive, Spark, Python, Natural language interfaces, Agentic AI tools, AI-powered platforms, Self-service analytics, AI agents, AI code generation, Data pipelines, Automated data classification, ETL pipelines