Jobgether is seeking a Senior Data Engineer to join our team. You will be responsible for designing, building, and maintaining scalable data pipelines and systems to support data-driven initiatives across the organization. You will collaborate closely with data scientists, analysts, and stakeholders to ensure data is accurate, accessible, and actionable, contributing to improved data architecture, performance, and insights.

What You'll Do

Design, build, and maintain reliable data pipelines that process and transform large volumes of data from various sources using tools such as Azure Data Factory, AWS Glue, or Apache Airflow.
Implement and optimize ETL / ELT processes with Python, SQL, and PySpark, integrating data from APIs, SaaS systems, and on-premises sources.
Develop and manage data warehouses and data lakes (e.g., Snowflake, Azure Synapse, Redshift, ADLS, S3, Delta Lake) with attention to scalability, performance, and cost efficiency.
Implement data partitioning, clustering, indexing, and quality validation frameworks to enhance reliability and query performance.
Collaborate with data scientists, analysts, and BI teams to ensure seamless access to data for analysis and reporting through tools such as Power BI, Tableau, or Looker.
Support CI/CD integration and infrastructure-as-code deployment with Terraform or CloudFormation.
Monitor, troubleshoot, and continuously optimize data workflows for performance, scalability, and cost efficiency.
Document data pipelines, data models, and architectural decisions, promoting data engineering best practices and standards.

What We're Looking For

5–8 years of experience as a Data Engineer or in a related role, with a proven track record of building and maintaining data systems.
Advanced experience with cloud ecosystems (Azure: ADF, Synapse, ADLS, Databricks; AWS: Glue, Redshift, S3, Lambda).
Strong programming skills in Python, SQL, and PySpark.
Hands-on experience with ETL / ELT pipeline design, optimization, and maintenance.
Knowledge of data modeling, database design, and big data technologies.
Experience integrating data with BI and analytics tools, including Power BI, DAX, and data cataloging tools.
Strong problem-solving, analytical thinking, and attention to detail.
Excellent collaboration and communication skills for working with cross-functional teams and explaining technical concepts to non-technical stakeholders.
Degree in Computer Science, Engineering, Data Science, or a related field, or equivalent professional experience.

Technical Stack

Data Orchestration: Azure Data Factory, AWS Glue, Apache Airflow
Programming & Query: Python, SQL, PySpark
Data Storage & Warehousing: Snowflake, Azure Synapse, Redshift, ADLS, S3, Delta Lake
BI & Analytics: Power BI, Tableau, Looker
Infrastructure as Code: Terraform, CloudFormation
Additional Technologies: Databricks, Lambda