Description

Responsibilities:

• Defines data requirements, gather, and wrangle large scale of structured and unstructured data, and validate data by running various data tools in the Data Environment.

• Supports the standardization, customization, and ad-hoc data analysis, and will develop the mechanisms to ingest, analyze, validate, normalize and clean data.

• Creates data policy and develop interfaces and retention models which requires synthesizing or anonymizing data.

• Implements statistical data quality procedures on new data sources, and by applying rigorous iterative data analytics, supports Data Scientists and analytics and insights creation in data sourcing and preparation to visualize data and synthesize insights of commercial value.

• Develops and maintains data engineering best practices and contributes to Insights on data analytics and visualization concepts, methods and techniques.

• Works closely with the data science and business intelligence teams to develop data models and pipelines for research, reporting, and machine learning.

• Design, implement, and support scalable data infrastructure solutions to integrate with multi-heterogeneous data sources, aggregate and retrieve Big Data in a fast and safe mode, curate data that can be used in BI reporting, analysis, machine learning models and ad-hoc data requests.

• Build data pipelines that clean, transform, and aggregate data from disparate sources.

• Engages with business teams to gather requirements and design data solutions.

• Mentors team of more Junior Data Engineers.

• Collaborates across multiple projects to provide data engineering expertise across teams.

• Analyzes most relevant insights and shares with leadership to provide strategic recommendations for the business • Lead a team of data engineers and act as a key senior contributor to a data engineering project.

Skills and Experience:

• 7+ years of overall IT experience

• 5+ years of experience in a data engineering/ETL role with a track record of manipulating, processing, and extracting value from large datasets • 3+ years of experience with Big Data tools/technologies like Hadoop, Spark, Spark SQL, Kafka, Sqoop, Hive, S3, HDFS, or Cloud platforms e.g. AWS, GCP, etc.

• 3+ years building, testing, and optimizing data ingestion pipelines, architectures, and data sets with Tibco, IBM or others.

• Databricks UI, Managing Databricks Notebooks, Delta Lake with Python, Delta Lake with Spark SQL, Delta Live Tables, Unity Catalog.

• High-velocity high-volume stream processing with Apache Kafka and Spark Streaming.

• Strong SQL skills with ability to write intermediate complexity queries.

• ETL experience with PySpark, Spark SQL , IBM Data Stage or similar.

• Agile Scrum, Kanban or SAFe experience.

Skills Desired

• Databricks, Python (and/or Scala) and PySpark/Scala-Spark.

• Database solutions like Databricks, Teradata, Mainframe, DB2 or BigQuery.

• BI Solutions like Spotfire, OAC, Tableau or PowerBI • Azure, AWS Serverless technologies, like, S3, Kinesis/MSK, lambda, and Glue.

• Messaging Platforms like Kafka, Amazon MSK & TIBCO EMS or IBM MQ Series.

• Strong SQL skills with ability to write intermediate complexity queries • Experience with GIT code versioning software

Key Skills

Education

Bachelor's degree