Data Engineer

Location: Prakāshamnagar

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
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
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:

Minimum

Experience of 6-9 years
Must have

Skills:

Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, Spark

SQL), workflow orchestration, performance tuning on big data processing
Proficiency in data analysis tools (eg. SQL)
Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data stores

Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development
Strong understanding of data modeling, data warehousing, and data integration concepts
Proven ability to optimize query performance on big data platforms

Preferred Qualifications:

Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing
Knowledge of Python/R, Databricks, cloud data platforms
Strong understanding of data governance frameworks, tools, and best practices.
Knowledge of data protection regulations and compliance requirements (e. g. , GDPR, CCPA)
Professional

Certifications:

AWS Certified Data Engineer preferred
Databricks Certificate preferred
Soft Skills  :
Excellent critical-thinking and problem-solving skills
Strong communication and collaboration skills
Demonstrated awareness of how to function in a team setting
Demonstrated presentation skills