Senior Data Engineer

Role:

Mandatory Skills:

Notice Period:

Experience Range:

Location:

Budget:

Job Overview

Senior Data Engineer

Key Responsibilities

Data Ingestion Framework

• Design & Development:

  Architect, develop, and maintain an end-to-end data ingestion framework that efficiently extracts, transforms, and loads data from diverse sources.

• Framework Optimization:

  Use AWS services such as AWS Glue, Lambda, EMR, ECS, EC2, and Step Functions to build highly scalable, resilient, and automated data pipelines.

Data Quality & Validation

• Validation Processes:

  Develop and implement automated data quality checks, validation routines, and error-handling mechanisms to ensure the accuracy and integrity of incoming data.

• Monitoring & Reporting:

  Establish comprehensive monitoring, logging, and alerting systems to proactively identify and resolve data quality issues.

API Development

• Design & Implementation:

  Architect and develop secure, high-performance APIs to enable seamless integration of data services with external applications and internal systems.

• Documentation & Best Practices:

  Create thorough API documentation and establish standards for API security, versioning, and performance optimization.

Collaboration & Agile Practices

• Cross-Functional Communication:

  Work closely with business stakeholders, data scientists, and operations teams to understand requirements and translate them into technical solutions.

• Agile Development:

  Participate in sprint planning, code reviews, and agile ceremonies, while contributing to continuous improvement initiatives and CI/CD pipeline development (using tools like GitLab).

Required Qualifications

Experience & Technical Skills

• Professional Background:

  At least 5 years of relevant experience in data engineering with a strong emphasis on analytical platform development.

• Programming Skills:

  Proficiency in Python and/or PySpark, SQL for developing ETL processes and handling large-scale data manipulation.

• AWS Expertise:

  Extensive experience using AWS services including AWS Glue, Lambda, Step Functions, and S3 to build and manage data ingestion frameworks.

• Data Platforms:

  Familiarity with big data systems (e.g., AWS EMR, Apache Spark, Apache Iceberg) and databases like DynamoDB, Aurora, Postgres, or Redshift.

• API Development:

  Proven experience in designing and implementing RESTful APIs and integrating them with external and internal systems.

• CI/CD & Agile:

  Hands-on experience with CI/CD pipelines (preferably with GitLab) and Agile development methodologies.

Soft Skills

• Strong problem-solving abilities and attention to detail.
• Excellent communication and interpersonal skills with the ability to work independently and collaboratively.
• Capacity to quickly learn and adapt to new technologies and evolving business requirements.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• Experience with additional AWS services such as Kinesis, Firehose, and SQS.
• Familiarity with data lakehouse architectures and modern data quality frameworks.
• Prior experience in a role that required proactive data quality management and API-driven integrations in complex, multi-cluster environments.
• Adherence to Information Security Management policies and procedures.