About the Role

We are seeking an experienced IT Data Engineer to design, develop, and optimize data pipelines, ensuring seamless data integration and management within our IT infrastructure. This role is critical to driving the performance of our data systems and supporting business intelligence efforts across multiple platforms.

Your Profile

• Qualifications: Bachelor's degree in Computer Science, Information Technology, Data Science, or related field. A Master’s degree is an advantage but not mandatory.
• Experience: 3-7 years of hands-on experience in data engineering, building and managing data pipelines and workflows.
• Key Skills:
• Data Pipeline Development & Maintenance
• ETL/ELT Processes (Extract, Transform, Load)
• Data Integration & Management
• Cloud Computing (AWS, Azure, Google Cloud)
• Big Data Technologies (Hadoop, Spark, Kafka)
• Data Security & Compliance (GDPR, HIPAA)
• Data Quality & Governance
• Programming (Python, SQL, Scala)
• Languages: Proficiency in English (additional language proficiency is a plus).

Your Responsibilities

• Design and develop scalable data pipelines for efficient data ingestion, transformation, and storage.
• Ensure seamless data integration across multiple data sources (structured and unstructured).
• Collaborate with business and IT teams to optimize data processes and deliver high-quality data solutions.
• Implement CI/CD pipelines for automated data workflows and continuous integration.
• Ensure data security by following best practices and compliance regulations (e.g., GDPR, HIPAA).
• Monitor data quality, ensuring accuracy, completeness, and adherence to governance policies.
• Troubleshoot and resolve data performance issues in processing workflows and databases.
• Stay current with advancements in data engineering and cloud technologies, recommending new tools and techniques.

What We Offer

• A dynamic and innovative work environment focused on leveraging cutting-edge technologies.
• Opportunities to work with diverse teams and lead impactful data engineering projects.
• A collaborative team atmosphere where your contributions directly impact business success.

Next Steps

• Upload your resume via our ATS platform.
• Shortlisted candidates will be contacted within 5-7 working days for further discussions.

Skills

Key Skills

• Data Pipeline Development & Maintenance: Expertise in building and maintaining scalable ETL/ELT data pipelines to ensure efficient data flow across systems.
• ETL/ELT Processes: Strong understanding of Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes for data ingestion, transformation, and storage.
• Data Integration: Proficiency in integrating data from diverse sources, including structured and unstructured data.
• Cloud Platforms: Experience with cloud technologies like AWS, Azure, or Google Cloud for data storage and processing (e.g., AWS Glue, Redshift, BigQuery).
• Big Data Technologies: Knowledge of distributed processing frameworks like Apache Hadoop, Apache Spark, and Apache Kafka for managing and processing large datasets.
• Programming Languages: Proficiency in programming languages such as Python, SQL, and Scala for data manipulation and automation tasks.
• Data Warehousing: Experience working with data warehouses like Snowflake, Redshift, or Google BigQuery to store and analyze large datasets.
• CI/CD Pipelines: Familiarity with continuous integration and continuous deployment (CI/CD) practices for automating data workflows.
• Data Security & Compliance: Knowledge of best practices for data security and compliance regulations, such as GDPR and HIPAA.
• Data Governance: Experience in ensuring data quality, integrity, and consistency through data governance strategies and monitoring tools.
• Performance Optimization: Ability to troubleshoot, optimize, and scale data processing workflows for efficiency and cost-effectiveness.
• Collaboration & Communication: Strong communication skills to work cross-functionally with business stakeholders, analysts, and IT teams.
• Problem-Solving: Analytical mindset with the ability to identify and resolve issues related to data processing and workflow performance.