Data Engineer

We are looking for an experienced Data Engineer to join our team and play a key role in building data pipelines, developing solutions, and optimizing data workflows to support our analytical and operational needs.

Job Description:

We are seeking a talented Data Engineer to join our growing data team. You will be responsible for designing, implementing, and managing efficient ETL processes, ensuring data is readily available and optimized for consumption by business stakeholders. You will work closely with cross-functional teams to enable data-driven decision-making across the organization.

Key Responsibilities:

• Design, implement, and maintain scalable and efficient ETL processes to integrate data from various sources into a centralized data warehouse.
• Build and manage data pipelines for continuous data ingestion, transformation, and reporting.
• Work with AWS services (specifically Redshift, S3, Lambda, Glue, etc.) to manage and optimize data storage and data flow architecture.
• Develop and optimize SQL queries and scripts for data extraction, transformation, and loading into data warehouses.
• Ensure the performance, quality, and security of the data platform.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions to meet those needs.
• Troubleshoot, monitor, and resolve any data pipeline issues or performance bottlenecks.
• Optimize the use of cloud infrastructure and design for scalability and cost-efficiency.
• Automate manual data tasks to improve efficiency and reliability.

Required Skills & Qualifications:

• Mandatory: Proven experience with ETL processes, Redshift, and AWS.
• Expertise in Amazon Web Services (AWS), including but not limited to Redshift, S3, Lambda, Glue, and EC2.
• Solid experience in designing and implementing data pipelines and managing large-scale data sets.
• Proficient in writing complex SQL queries and working with relational databases (e.g., Redshift, PostgreSQL, MySQL).
• Hands-on experience with AWS Redshift for data warehousing, performance tuning, and optimization.
• Strong understanding of cloud architectures and best practices for cloud data management.
• Familiarity with Python, Spark, or other data processing frameworks is a plus.
• Experience with data modeling, data transformation, and data integration techniques.
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.

Preferred Skills:

• Experience with containerization technologies like Docker and Kubernetes.
• Knowledge of data lake and data warehouse architectures.
• Experience with Apache Airflow, dbt (Data Build Tool), or similar orchestration tools.
• Familiarity with Agile/Scrum methodologies and CI/CD practices.
• Exposure to machine learning pipelines and supporting data-driven AI projects.