As a Senior Data Engineer, you shall be a part of our growing team of MI specialists. As a team leader, you will be evolving and optimizing our data and data pipeline architecture, as well as, optimizing data flow and collection for cross functional teams. You are an expert data pipeline builder and data wrangler who enjoys optimizing data systems and evolving them!

You will

• Define the business metrics of success for DE projects and translates them into performance or scalability metrics.
• Design and implement the data platform; and build a reporting and analytics engine/platform
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and cloud-based big data technologies from AWS, Azure and others.

To be successful in the role you must have

• Bachelors/Masters/Ph.D. in Computer Science, Information Systems, Data Science, Artificial Intelligence, Machine Learning, Electrical Engineering or related disciplines.
• Overall industry experience of around 10+ years, at least 5 years experience as a Data Engineer.

5 plus years of experience in the following:

• Software/tools: Hadoop, Spark, Kafka, etc.
• Relational SQL and NoSQL databases, including Postgres and Cassandra.

• Data and Model pipeline and workflow management tools: Azkaban, Luigi, Airflow, Dataiku, etc.
• Stream-processing systems: Storm, Spark-Streaming, etc.
• Object-oriented/object function scripting languages: Python, Java, Scala (Advanced level in one language, at least)
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and seek opportunities for improvement.
• Experience in Data warehouse design and dimensional modeling

• Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of other databases/date-sources.