Description

Job Overview:

We are looking for an experienced Data Engineer to join our growing team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and architectures to support data processing, analytics, and business intelligence efforts. You will work closely with data scientists and business analysts to ensure data availability and quality for analytical purposes.

Key Responsibilities:

Data Pipeline Development: Design, implement, and maintain efficient and scalable data pipelines to collect, process, and store data.

Data Integration: Integrate data from various sources (internal and external) to create unified datasets for analytics and reporting.

Database Management: Build and maintain databases and data warehouses to ensure smooth data flow and accessibility.

Data Quality & Performance Optimization: Ensure data consistency, integrity, and quality, and optimize performance for faster data retrieval and processing.

Collaboration with Data Scientists & Analysts: Work closely with data scientists, analysts, and other stakeholders to provide clean, structured data that supports business decisions.

Automation: Automate repetitive tasks and data workflows to improve efficiency and reduce errors.

Documentation: Maintain comprehensive documentation for data architectures, workflows, and processes.

Qualifications:

Bachelor’s Degree in Computer Science, Engineering, or a related field.

3+ years of experience in data engineering or a related role.

Strong experience with SQL, Python, ETL tools, and data pipeline frameworks (e.g., Apache Kafka, Apache Spark, Airflow).

Proficiency with cloud platforms like AWS, Azure, or Google Cloud.

Familiarity with data warehousing concepts and technologies (e.g., Redshift, Snowflake, BigQuery).

Preferred Skills:

Experience with NoSQL databases (e.g., MongoDB, Cassandra).

Knowledge of data modeling and data architecture principles.

Familiarity with containerization technologies (e.g., Docker, Kubernetes).

Experience with machine learning concepts and their integration into data pipelines

Key Skills

Education

Any Graduate