Key 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

Bachelors degree or higher in an analytical area such as Computer Science, Physics, Mathematics, Statistics, Engineering or similar.
3+ years relevant professional experience in Data Engineering and Business Intelligence
3+ 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.

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