Responsibilities

As an experienced member of the team, in this role, you will:

• Contribute to evolving the technical direction of analytical Systems and play a critical role their design and development
• You will research, design and code, troubleshoot and support. What you create is also what you own.
• You will focus on performance, cost efficiency, reliability, security and high availability of the products/modules and features that you own.
• Develop the next generation of automation tools for monitoring and measuring data quality, with associated user interfaces.
• Be able to broaden your technical skills and work in an environment that thrives on creativity, efficient execution, and product innovation.
  
  
  

Basic Qualifications

• Bachelor’s degree or higher in an analytical area such as Computer Science, Physics, Mathematics, Statistics, Engineering or similar.
• 5+ years relevant professional experience in Data Engineering and Business Intelligence
• 5+ years in with Advanced SQL (analytical functions, window functions, Rollups/Cubes, Complex joins, Complex scanning methods and Join methods), ETL, Data Warehousing.
• Strong knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures, data modeling and performance tuning.
• Ability to effectively communicate with both business and technical teams.
• Excellent coding skills in Java, Python, C++, or equivalent object-oriented programming language
• Understanding of relational and non-relational databases & data stores
• Proficiency with at least one of these scripting languages: Perl / Python / Ruby / shell script
  
  
  

Preferred Qualifications

• Experience with building data pipelines from application databases.
• Experience with AWS services - S3, Redshift Spectrum, EMR, Glue, Athena, ELK, AWS lambda and Step functions.
• Experience working with Data Lakes & Data Mesh.
• Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space.
• Sharp problem-solving skills and ability to resolve ambiguous requirements.
• Experience on working with both structured & unstructured data at Big Data volume and internet scale.
• Knowledge and experience on working with Hive, Spark, Kafka & the Hadoop ecosystem.
• Knowledge and experience on coding with Pyspark, SparQL.
• Experience working with Data Science teams.