
Posted 1 month ago
Associate Data Engineer
AI Summary
Designs, builds, and maintains data pipelines and ETL processes to transform large datasets into actionable insights, supporting business decisions and data governance initiatives.
About this role
Career Category
Information SystemsJob Description
Role Description:
The role is responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes
Roles & Responsibilities:
Design, develop, and maintain data solutions for data generation, collection, and processing
Be a key team member that assists in design and development of the data pipeline
Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems
Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions
Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks
Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs
Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency
Implement data security and privacy measures to protect sensitive data
Very good understanding of Databricks
Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
Collaborate and communicate effectively with product teams
Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
Identify and resolve complex data-related challenges
Adhere to best practices for coding, testing, and designing reusable code/component
Explore new tools and technologies that will help to improve ETL platform performance
Participate in sprint planning meetings and provide estimations on technical implementation
Basic Qualifications and Experience:
Bachelor’s degree and 2 to 4 years of Computer Science, IT or related field experience
Functional Skills:
Must-Have Skills
Proficiency in Databricks ,Python, PySpark, and Scala for data processing and ETL (Extract, Transform, Load) workflows, with hands-on experience in using Databricks for building ETL pipelines and handling big data processing
Strong knowledge of SQL and experience with relational (e.g., PostgreSQL, MySQL) databases.
Familiarity with big data frameworks like Apache Hadoop, Spark, and Kafka for handling large datasets.
Good-to-Have Skills:
Experience with cloud platforms such as AWS particularly in data services (e.g., EKS, EC2, S3, EMR, RDS, Redshift/Spectrum, Lambda, Glue, Athena)
Understanding of data modeling, data warehousing, and data integration concepts
Understanding of machine learning pipelines and frameworks for ML/AI models
Skills
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