Data Engineer

We are seeking an experienced and highly skilled Senior Data Engineer to join our growing data team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines, optimizing data infrastructure, and enabling efficient data access for analytics, reporting, and machine learning initiatives. You will collaborate closely with data analysts, data scientists, software engineers, and business stakeholders to deliver reliable and high\-quality data solutions.

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines for processing large\-scale datasets.


• Build and manage scalable data warehouses, data lakes, and data marts.


• Develop data integration solutions from multiple internal and external sources.


• Ensure data quality, integrity, security, and governance across systems.


• Optimize database performance, query execution, and data storage solutions.


• Implement monitoring, troubleshooting, and performance tuning of data pipelines.


• Collaborate with cross\-functional teams to understand data requirements and business objectives.


• Support business intelligence and analytics teams with reliable data infrastructure.


• Mentor junior data engineers and promote engineering best practices.


• Stay updated with emerging technologies and recommend improvements to the data ecosystem.

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.


• 5\+ years of experience in data engineering or related roles.


• Strong proficiency in SQL and database design principles.


• Experience with Python, Java, Scala, or similar programming languages.


• Hands\-on experience with ETL/ELT tools and data pipeline development.


• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.


• Knowledge of data warehousing concepts and big data technologies.


• Familiarity with version control systems such as Git.

• Experience with Apache Spark, Hadoop, Kafka, Airflow, or Databricks.


• Knowledge of containerization technologies such as Docker and Kubernetes.


• Understanding of data governance, security, and compliance requirements.


• Experience supporting machine learning and advanced analytics workloads.


• Strong problem\-solving and communication skills.

• Competitive salary package.


• Performance\-based bonuses.


• Health, dental, and vision insurance.


• Flexible work arrangements and remote work options.


• Generous paid time off and company holidays.


• Professional development and certification support.


• Employee wellness programs.


• Retirement savings plan/pension contributions.


• Collaborative and innovative work environment.


• Career growth and leadership opportunities.

Benefits:

• Bereavement leave


• Canteen


• Free parking


• Life insurance


• On\-site parking


• Sick pay

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