The Role
Designs and maintains AWS data architectures, ETL/ELT pipelines, data warehouses, analytics datasets, dashboards, and visualization solutions. Uses SQL, Python, Spark, Glue, Lambda, S3, Athena, Redshift, and QuickSight to prepare, transform, validate, and govern data. Collaborates with product, engineering, and operations teams, optimizing performance, cost, scalability, and data quality while integrating data systems with AI and natural-language query tools.
Summary Generated by Built In
About QualMinds:
We at QualMinds design & develop world-class digital products and custom software for Startups, Scale- ups & Enterprises with our world-class engineering team. We assemble a great team of frontend, backend, full-stack, QA automation, UI/UX, DevOps, data science, machine learning, and agile experts to help our clients propel their pursuit of digital excellence. Our engineering community at QualMinds is always passionate about building customer-centric software with the highest quality, performance, security, scalability, and lowest failure rates.
Role Overview:
The AWS Data Engineer will support the design, development, and maintenance of reporting and analytics solutions. This includes building dashboards and reports, preparing and validating data for analysis, supporting data models and pipelines, and working with cross-functional teams to turn business questions into clear, actionable insights.
Core Technical Responsibilities:
- Design and maintain scalable data architectures on AWS.
- Build and manage data pipelines (ETL/ELT) using AWS Glue, Lambda, S3, and Athena.
- Model and optimize data warehouses (primarily Amazon Redshift).
- Implement and manage data visualization and self-service analytics (e.g., AWS QuickSight).
- Develop and maintain data transformation processes using SQL, Python, and Apache Spark.
- Establish and enforce data governance, documentation, and data quality standards.
- Optimize data performance, cost efficiency, and scalability across environments.
- Collaborate with product, engineering, and operations teams to deliver analytics-ready datasets.
- Integrate data systems with AI tools for natural language and dashboarding functionality.
Required Technical Skills:
- 2+ years in Business Intelligence reporting preferably AWS QuickSight.
- Deep expertise in AWS data stack (Redshift, Glue, Lambda, S3, Athena).
- Strong SQL and Python skills for data manipulation and automation.
- Experience with Apache Spark for large-scale data processing.
- Experience with data visualization tools, preferably AWS QuickSight.
Preferred Skills:
- Experience in startups or fast-scaling tech environments.
- Familiarity with workflow orchestration tools (e.g., Airflow, Step Functions).
- Understanding of AI/ML data interfaces or natural language query tools.
Skills Required
- 2+ years of business intelligence reporting experience, preferably with AWS QuickSight
- Deep expertise in the AWS data stack, including Redshift, Glue, Lambda, S3, and Athena
- Strong SQL and Python skills for data manipulation and automation
- Experience with Apache Spark for large-scale data processing
- Experience with data visualization tools, preferably AWS QuickSight
- Experience in startups or fast-scaling technology environments
- Familiarity with workflow orchestration tools such as Airflow or Step Functions
- Understanding of AI/ML data interfaces or natural-language query tools
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The Company
What We Do
We design & develop world-class digital products and custom software for Startups, Scale-ups & Enterprises with our world-class engineering team. We assemble a great team of frontend, backend, full-stack, QA automation, UI/UX, DevOps, data science, machine learning, and agile experts to help our clients propel their pursuit of digital excellence. Our engineering community at QualMinds is always passionate about building customer-centric software with the highest quality, performance, security, scalability, and lowest failure rates
