Data Engineer – AWS Data Platform

DICETEK LLC; Abu Dhabi; Presencial; AED 250.000 - 420.000; Jornada completa

Descripción de la vacante

DICETEK LLC seeks a Senior Data Engineer to design and operate enterprise-grade data pipelines in a secure AWS data lakehouse environment. You will implement ETL/ELT processes, leverage PySpark and SQL, and ensure data quality, governance and scalable architecture within banking/financial services contexts.

The role requires hands-on experience with AWS Glue, Redshift, Athena, Lake Formation, and Iceberg, plus CI/CD and collaboration via Jira/Confluence in an Agile setting.

Formación

• Strong hands-on experience delivering enterprise-scale data engineering solutions on AWS.
• Strong development experience with Python/PySpark, SQL and AWS data services.
• Experience designing and developing ETL/ELT and data ingestion pipelines for enterprise systems.
• Experience with Glue Catalog, Redshift, Athena and Lake Formation in data lakehouse environments.
• Understanding of data governance, security, regulatory requirements and IAM controls.

Conocimientos

AWS

Python

PySpark

SQL

Data engineering

Data modeling

Data governance

IAM & security controls

QA & data quality

CI/CD

GitHub Actions

Jira

Confluence

Herramientas

AWS Glue

Amazon Redshift

Amazon Athena

AWS S3

AWS Lake Formation

Apache Iceberg

APIs

Relational databases

Streaming data sources

GitHub

Jenkins

Descripción del empleo

Job Location Abu Dhabi (Work From Office)

Job Type Contract

Job Description

Years of Experience *

Required Skills *

• Strong hands-on experience delivering enterprise-scale data engineering solutions on AWS.
• Strong development experience with:
• Python / PySpark
• SQL
• AWS Glue
• AWS S3
• Strong experience designing and developing ETL/ELT and data ingestion pipelines.
• Experience working with:
• AWS Glue and Glue Catalog
• Amazon Redshift
• Amazon Athena
• AWS Lake Formation
• Apache Iceberg or similar open table formats
• Good understanding of:
• Data lake / lakehouse architecture
• Data warehousing
• Dimensional and analytical data modelling
• Data partitioning and optimisation
• Metadata management and data lineage
• Strong understanding of data quality, reconciliation and validation techniques.
• Experience integrating data from multiple source technologies, such as:
• Relational databases
• APIs
• Streaming/event-based sources
• Experience troubleshooting complex data and pipeline issues.
• Good understanding of IAM, security and data-access controls within AWS.
• Experience with version control and CI/CD using tools such as:
• GitHub
• Jenkins
• GitHub Actions
• Experience working within Agile delivery environments using JIRA and Confluence.

Required Experience / Knowledge Areas *

• Strong professional experience in Data Engineering and Enterprise Data Platforms.
• Demonstrable experience delivering production-grade data pipelines in complex enterprise environments.
• Experience working within Banking or Financial Services strongly preferred.
• Understanding of data governance, security and regulatory requirements within a controlled enterprise environment.
• Experience working across the full engineering lifecycle from requirements and source-data analysis through development, testing, deployment and production support.