Data Engineer

Data Engineer

Key Responsibilities:

• Design, develop, and maintain robust, scalable, and high-performance

  data pipelines

  .
• Work closely with Data Scientists and Analysts to support

  data preparation, model deployment, and monitoring

  .
• Implement and manage

  MLOps frameworks

  using tools such as

  MLflow, SageMaker, or similar platforms

  .
• Integrate

  APIs

  and external data sources to ensure seamless data ingestion and transformation.
• Optimize SQL queries and database structures for performance and scalability.
• Define and track

  KPIs (Key Performance Indicators)

  for data quality, system performance, and pipeline reliability.
• Collaborate with cross-functional teams to support business analytics, AI/ML, and reporting needs.
• Ensure compliance with data governance, privacy, and security standards.

Required Skills & Qualifications:

• Bachelor's or Master's degree

  in Computer Science, Data Engineering, Information Technology, or a related field.
• Minimum

  5 years of experience

  in

  data engineering

  or a related role.
• Strong programming skills in

  Python

  and

  SQL

  .
• Proficient in developing and managing

  APIs

  for data integration.
• Hands-on experience with

  MLOps tools

  (e.g.,

  MLflow

  ,

  SageMaker

  ,

  Kubeflow

  , or

  Airflow

  ).
• Experience with

  cloud platforms

  such as AWS, Azure, or GCP.
• Proven track record in

  KPI design and implementation

  for monitoring data systems.
• Solid understanding of

  ETL processes

  ,

  data modeling

  , and

  data warehouse

  concepts.
• Familiarity with version control tools (e.g., Git) and CI/CD pipelines.