We are seeking an experienced Senior Data Engineer to lead the development of a scalable data ingestion framework while ensuring high data quality and validation. The successful candidate will also be responsible for designing and implementing robust APIs for seamless data integration. This role is ideal for someone with deep expertise in building and managing big data pipelines using modern AWS-based technologies, and who is passionate about driving quality and efficiency in data processing systems.
/ Duties and Responsibilities
Architect, develop, and maintain end-to-end data ingestion framework for extracting, transforming, and loading data from diverse sources
Use AWS services (Glue, Lambda, EMR, ECS, EC2, Step Functions) to build scalable, resilient automated data pipelines
Develop and implement automated data quality checks, validation routines, and error-handling mechanisms
Establish comprehensive monitoring, logging, and alerting systems for data quality issues
Architect and develop secure, high-performance APIs for data services integration
Create thorough API documentation and establish standards for security, versioning, and performance
Work with business stakeholders, data scientists, and operations teams to understand requirements
Participate in sprint planning, code reviews, and agile ceremonies
Contribute to CI/CD pipeline development using GitLab
Job Specification / Skills and Competencies
5+ years experience in data engineering with analytical platform development focus
Proficiency in Python and/or PySpark
Strong SQL skills for ETL processes and large-scale data manipulation
Extensive AWS experience (Glue, Lambda, Step Functions, S3)
Familiarity with big data systems (AWS EMR, Apache Spark, Apache Iceberg)
Database experience with DynamoDB, Aurora, Postgres, or Redshift
Proven experience designing and implementing RESTful APIs
Hands-on CI/CD pipeline experience (preferably GitLab)
Agile development methodology experience
Strong problem-solving abilities and attention to detail
Excellent communication and interpersonal skills
Ability to work independently and collaboratively
Capacity to quickly learn and adapt to new technologies
10+ years total experience
Any Additional Information/Specifics
Bachelor's/Master's in Computer Science, Data Engineering or related field (preferred)
Experience with additional AWS services (Kinesis, Firehose, SQS)
Familiarity with data lakehouse architectures and modern data quality frameworks
Experience with proactive data quality management in multi-cluster environments
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