Role Description:
The
Data Engineer
is responsible for designing, building, and maintaining data infrastructure and pipelines that enable reliable data collection, transformation, and analysis across the organization. This role ensures that data systems are scalable, efficient, and aligned with business objectives. Working closely with data scientists, analysts, and software engineers, the
Data Engineer
supports data-driven decision-making through the delivery of clean, structured, and accessible datasets.
This position is ideal for technically skilled and detail-oriented professionals who enjoy solving complex problems, optimizing data processes, and working with modern data technologies.
Key Responsibilities:
* Design, develop, and maintain robust data pipelines and ETL processes to collect, process, and store large datasets from multiple sources.
* Build and manage data architectures that ensure scalability, performance, and data quality.
* Collaborate with analysts and data scientists to understand data needs and implement solutions that support analytics and machine learning models.
* Optimize data workflows and automate data ingestion, transformation, and validation tasks.
* Implement data governance practices, ensuring compliance with internal standards and privacy regulations.
* Develop data models and schemas to support business intelligence and reporting requirements.
* Monitor data systems to ensure reliability, availability, and integrity.
* Collaborate with DevOps teams to manage cloud-based data environments and CI/CD pipelines.
* Document system architecture, workflows, and data definitions.
* Stay up to date with new tools, technologies, and best practices in data engineering.
Qualifications:
* Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
* 2–5 years of experience in data engineering, data warehousing, or database development.
* Proficiency in programming languages such as Python, Java, or Scala.
* Strong experience with SQL and relational as well as non-relational databases.
* Familiarity with data processing frameworks (e.g., Apache Spark, Kafka, Flink, or Airflow).
* Experience with cloud platforms such as AWS, Azure, or Google Cloud and their respective data services (e.g., Redshift, BigQuery, or Snowflake).
* Knowledge of ETL design, data modeling, and API integration.
* Understanding of version control systems (Git) and CI/CD workflows.
* Strong analytical, problem-solving, and troubleshooting abilities.
* Excellent collaboration and communication skills.
* Fluency in English required; additional languages are a plus.
As a
Data Engineer
, you will play a key role in building the data foundation that powers analytics, insights, and innovation. This position offers the opportunity to work with cutting-edge technologies, shape data strategy, and contribute to scalable solutions that support business transformation and intelligent decision-making.