(The primary tasks, functions and deliverables of the role)
- Design and build reusable components, frameworks and libraries at scale to support analytics products
- Design and implement product features in collaboration with business and Technology stakeholders
- Identify and solve issues concerning data management to improve data quality
- Clean, prepare and optimize data for ingestion and consumption
- Collaborate on the implementation of new data management projects and re-structure of the current data architecture
- Implement automated workflows and routines using workflow scheduling tools
- Build continuous integration, test-driven development and production deployment frameworks
- Collaboratively review design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
- Analyze and profile data for designing scalable solutions
- Troubleshoot data issues and perform root cause analysis to proactively resolve product and operational issues
- Lead and mentor team of data engineers
- Trouble shoot key issues and ensure team member performance
Requirements:
Experience:
- Strong understanding of data structures and algorithms
- Strong understanding of solution and technical design
- Has a strong problem solving and analytical mindset?
- Able to influence and communicate effectively, both verbally and written, with team members and business stakeholders
- Able to quickly pick up new programming languages, technologies, and frameworks
- Advanced experience building cloud scalable, real time and high-performance data lake solutions
- In-depth understanding of micro service architecture
- Strong understanding of developing complex data solutions
- Experience working on end-to-end solution design
- Able to lead others in solving complex problems by taking a broad perspective to identify innovative solutions
- Willing to learn new skills and technologies
- Has a passion for data solutions
Required and Preferred Skill Sets:
- 3+ years of hands-on expert level experience in AWS - EMR [Hive, Pyspark], S3, Athena or any other equivalent cloud
- 3+ years of hands-on expert level experience Spark Batch Processing and some familiarity with Spark Structured Streaming
- 3-4 years’ experience Working experience with Hadoop stack dealing huge volumes of data in a scalable fashion
- 5+ years of hands-on experience with SQL, ETL, data transformation and analytics functions
- 5+ years of hands-on Python experience including Batch scripting, data manipulation, distributable packages
- 5+ years’ experience working with batch orchestration tools such as Apache Airflow or equivalent
- 5+ years working with code versioning tools such as GitHub or BitBucket; expert level understanding of repo design and best practices
- 5+ years working with deployment automation tools such as Jenkins and familiarity with containerization concepts such as Docker and Kubernetes
- 5+ years of hands-on experience designing and building ETL pipelines; expert with data ingest, change data capture, data quality; hand on experience with API development; some exposure to Nifi or Kafka
- 5+ years designing and developing relational database objects; knowledgeable on logical and physical data modelling concepts; some experience with Snowflake
- 3+ years of experience supporting Tableau or Cognos use cases; familiarity with tools and capabilities
- Familiarity with Agile; working experience preferred