AWS Data Engineer / BI Engineer

About The Ksquare Group

The Ksquare Group is a global technology consulting company headquartered in Dallas, Texas, with over 14 years of experience delivering technology solutions across Salesforce, cloud, data, AI, and network engineering for clients in Banking & Financial Services, Public Sector, Telecommunications, Manufacturing, Logistics, Healthcare, and Enterprise Services.

About the Role

We are seeking a highly skilled AWS Data Engineer with BI Engineering expertise to design, build, and optimize scalable data platforms and business intelligence solutions. The ideal candidate will have strong experience in AWS cloud services, ETL/ELT development, data warehousing, data modeling, and BI reporting tools to enable data-driven decision-making across the organization.

The role involves working closely with business stakeholders, data architects, analysts, and application teams to develop robust data pipelines, analytical data models, and interactive dashboards that deliver actionable business insights.

Key Responsibilities

Data Engineering

• Design, develop, and maintain scalable ETL/ELT pipelines using AWS cloud technologies.
• Build and optimize data ingestion frameworks from multiple structured and unstructured data sources.
• Develop and maintain data lakes and data warehouses on AWS.
• Implement data cleansing, transformation, validation, reconciliation, and data quality frameworks.
• Create and maintain dimensional data models (Star/Snowflake schemas) for reporting and analytics.
• Ensure data security, governance, and compliance standards are followed.
• Optimize data pipelines for performance, scalability, and cost efficiency.
• Collaborate with DataOps teams for CI/CD implementation and deployment automation.

Business Intelligence

• Design, develop, and maintain dashboards, scorecards, and reports using BI tools.
• Translate business requirements into actionable KPI dashboards and analytical solutions.
• Develop semantic and reporting layers to support self-service analytics.
• Create data visualizations that provide meaningful business insights.
• Monitor and improve report performance and data accuracy.
• Partner with business stakeholders to understand reporting and analytics requirements.

Governance & Quality

• Define and measure data quality KPIs such as completeness, accuracy, consistency, and freshness.
• Support master data management and data governance initiatives.
• Implement data lineage and metadata management best practices.
• Ensure data reconciliation and validation against source systems.

Mandatory Skills

AWS & Cloud

• AWS Glue
• Amazon Redshift
• AWS Lambda
• Amazon S3
• AWS Athena
• AWS EMR
• AWS Step Functions
• AWS CloudWatch
• IAM & Security Services

Data Engineering

• Python
• PySpark
• SQL
• PostgreSQL
• ETL/ELT Development
• Data Warehousing
• Data Modeling
• Data Profiling & Cleansing
• Data Reconciliation
• Data Quality Management

BI & Analytics

• Power BI / Tableau / Amazon QuickSight
• Dashboard Development
• Data Visualization
• KPI Reporting
• Business Intelligence Solutions
• DAX (for Power BI) preferred

Orchestration & DevOps

• Apache Airflow
• Git/GitHub
• CI/CD Pipelines
• Agile/Scrum Methodology

Preferred Skills

• Snowflake or Databricks
• Knowledge of Azure or GCP cloud platforms
• Data Governance and Data Lineage tools
• Apache Spark, Hadoop, Hive
• API Integration (REST APIs)
• Data Masking and PII Compliance
• Machine Learning data pipeline exposure
• Infrastructure as Code (Terraform/CloudFormation)

Primary Skills: AWS, Redshift, Glue, Python, PySpark, SQL, Power BI/Tableau, Data Warehousing, ETL/ELT, Airflow

Secondary Skills: Snowflake, Databricks, QuickSight, Data Governance, CI/CD, API Integration.