What you’ll do

Key Responsibilities:

- Design and Build Data Pipelines:** Develop scalable data pipelines using AWS services like AWS Glue, Amazon Redshift, and S3.

- Create efficient ETL processes for data extraction, transformation, and loading into data warehouses and lakes.

- Build and manage applications using Python, SQL, Databricks, and various AWS technologies.

- Utilize QuickSight to create insightful data visualizations and dashboards.

- Quickly develop innovative Proof-of-Concept (POC) solutions to address emerging needs.

- Provide support and manage the ongoing operation of data services.

- Automate repetitive tasks and build reusable frameworks to improve efficiency.

- Work with teams to design and develop data products that support marketing and other business functions.

- Ensure data services are reliable, maintainable, and seamlessly integrated with existing systems.

Who you are

- Bachelor’s degree in Computer Science, Engineering, or a related field.

- Technical Skills:

- Proficiency in Python with Pandans, PySpark.

- Hands-on experience with AWS services including S3, Glue Lambda, API Gateway, and SQS.

- Knowledge of data processing tools like Spark, Hive, Kafka, and Airflow.

- Experience with batch job scheduling and managing data dependencies.

- Experience with QuickSight or similar tools.

- Familiarity with DevOps automation tools like GitLab, Bitbucket, Jenkins, and Maven.

- Understanding of Delta is would be an added advantage.

Preferred Skills:

- Experience with AWS Big Data services like Amazon EMR and Kinesis.

- Familiarity with containerization technologies like Docker and Kubernetes.

- Knowledge of data visualization tools such as Tableau or Power BI.