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About the Role
We are looking for a hands-on Data Engineer to support the development of enterprise analytics and reporting platforms using AWS cloud technologies.
This role focuses on building scalable ETL pipelines, transforming data for analytics consumption, and enabling business intelligence reporting through Amazon QuickSight dashboards.
You will work closely with business stakeholders, analysts, and engineering teams to deliver reliable and actionable data solutions.
Key Responsibilities
• Design, develop, and maintain ETL/ELT pipelines for ingesting and transforming data from multiple enterprise systems.
• Build and optimize datasets for reporting and analytics consumption using Amazon QuickSight.
• Develop scalable data workflows using AWS Glue, Amazon S3, Amazon Redshift, and related AWS services.
• Create and maintain data models, data marts, and reporting layers to support dashboards and analytics requirements.
• Collaborate with business users and analysts to understand reporting requirements and translate them into technical solutions.
• Optimize SQL queries, data transformations, and dashboard performance for scalability and responsiveness.
• Perform data validation, reconciliation, and quality checks to ensure data accuracy and consistency.
• Monitor and troubleshoot ETL jobs, reporting pipelines, and QuickSight datasets.
• Support deployment, enhancement, and maintenance of analytics platforms in cloud environments.
• Document data flows, transformation logic, dashboard structures, and technical processes.
Required Skills & Experience
• 3+ years of experience in Data Engineering, BI Engineering, or Analytics Engineering.
• Strong hands-on experience with Amazon QuickSight.
• Experience building ETL pipelines using AWS Glue and AWS cloud services.
• Strong SQL and Python skills for data transformation and automation.
• Experience with Amazon Redshift, Amazon S3, and relational databases.
• Familiarity with data warehousing concepts and dimensional modelling.
• Experience supporting reporting and dashboarding solutions for business users.
• Strong analytical and problem-solving skills.
Preferred Qualifications
• Experience working with large-scale enterprise or government data platforms.
• Familiarity with PySpark or Apache Spark.
• Experience with dashboard optimization and performance tuning in QuickSight.
• Exposure to AWS IAM, CloudWatch, and CI/CD workflows.
• Understanding of data governance, access controls, and security best practices.
Tech Stack
• Amazon QuickSight
• AWS Glue
• Amazon Redshift
• Amazon S3
• Python
• SQL
• PySpark
Why Join Us
• Opportunity to work on enterprise-scale analytics and reporting platforms.
• Exposure to modern AWS cloud and data engineering technologies.
• Collaborative environment with strong technical and business stakeholder engagement.
• Opportunity to drive data-driven decision-making through impactful dashboards and analytics solutions.
Job ID: 148492397
Skills:
C, Tensorflow, Pytorch, Python, Machine Learning Algorithms, wearable devices, Deep Learning frameworks, resource-efficient algorithms, Signal Processing, domain adaptation, human activity recognition, software pipelines, PPG sensing, heart rate estimation, wearable hardware prototypes
Skills:
python, traditional optimization methods, LLM APIs, LLM baseline methods, LLM alignment algorithm
Skills:
Data Governance, Python, compliance validation, data standards, consent management systems, R, data engineering tools, data sharing agreements
Skills:
Typescript, Javascript, Terraform, Python, AWS, GitLab CI, LLM integrations, RAG architectures
Skills:
Java, Hibernate, Google Cloud Platform, Maven, Spring Boot, Shell Scripting, J2EE, Sql, REST, Docker, Sftp, Rhel, Kubernetes, Spring Framework, File Transfer Protocol, Java Application Development, Computer Science, Internet Technologies, Job Scheduling
We don’t charge any money for job offers
