Design and deliver data warehouse architectures and establish reliable ETL/ELT workflows to maintain data quality and accessibility

Build and refine data pipelines leveraging AWS technologies such as Glue, Redshift, Athena, DynamoDB, and Amazon RDS

Develop and update automation scripts for pipeline operations, including Glue scripts for creating parameterized parquet files

Oversee the transition of data assets and workflows to the cloud, enabling the retirement of multi-platform BI solutions

Facilitate smooth data integration across a variety of platforms, sources, and formats to drive the adoption of a Data Mesh model

Work closely with engineers, analysts, and administrators to capture business requirements and deliver tailored data solutions

Collaborate with business stakeholders to clarify data needs, estimate project scope, and construct pipelines for Data Lake ingestion

Contribute to the creation of Redshift data models that power BI visualizations in Tableau Cloud or Server

Strengthen the BI environment while enabling the development of advanced ML, AI, and Deep Learning solutions

Prepare and maintain documentation for database structures, ETL/ELT processes, security models, and architectural diagrams

Uphold rigorous data governance practices to guarantee data reliability, protection, and accessibility

Construct Glue Data Pipelines to bring in data from APIs, transform it, and load it into cloud storage

Write Glue scripts to generate parameterized parquet files in JSON format and automate their storage in the cloud

Design and deploy Redshift data models for metrics to be visualized in Tableau

Support business teams in defining data requirements, estimating workloads, and delivering pipeline solutions for Data Lake integration

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

At least 5 years of hands-on experience in data engineering

Minimum one year of experience leading and managing technical teams

Demonstrated expertise with AWS data services, including S3, Glue, Redshift, Lambda, DynamoDB, Athena, and RDS

In-depth knowledge of ETL/ELT processes, data pipeline design, and contemporary data warehousing principles

Proficiency in programming languages such as Python, SQL, or Scala

Experience building, deploying, and tuning data models in Redshift or comparable platforms

Strong analytical and troubleshooting abilities with a keen eye for detail

Excellent interpersonal skills and a proven ability to work effectively with both technical and business teams

Advanced English proficiency, both written and spoken, at B2+ level or above

Experience with data visualization platforms, particularly Tableau Server or Tableau Cloud

Background in implementing Data Mesh architectures

Understanding of machine learning, deep learning, AI, and IoT technologies

Familiarity with big data tools like Apache Spark and Hadoop

Knowledge of JSON schema design and managing cloud storage

Hands-on experience with AWS Lambda and Amazon EC2