Data Engineer (Remote)

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.