Data Engineer - Databricks

Overview

We are looking for seasoned Data Engineer to work with our team and our clients to develop enterprise grade data platforms, services, and pipelines. We are looking for more than just a "Data Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Responsibilities

• Lead and architect data pipelines and ingest patterns to move raw data from data producers to an enterprise data ecosystem, with a focus on performance and reliability
• Assess and understand the ETL jobs, workflows, BI tools, and reports
• Address technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products
• Experience in crafting database / data warehouse solutions in cloud (Preferably AWS. Alternatively Azure, GCP).
• Key must have skill sets – Python, SQL, Databricks, AWS Data Services
• Support an Agile software development lifecycle
• You will contribute to the growth of our Data Exploitation Practice!

Qualifications

• Experience supporting ICE contract work.
• Experience working in Design Intelligence.
• Bachelor’s Degree and 6+ years of total experience or equivalent experience and education.
• 6+ years direct experience in Data Engineering with experience in tools such as:
• Big data tools: Hadoop, Spark, Kafka, etc.
• Relational SQL and NoSQL databases, including Postgres and Cassandra.
• Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• AWS cloud services: EC2, S3, RDS, Glue, Step Functions, Lamda, EMR, DynamoDB, DocumentDB, Redshift, Aurora, Athena
• Data Platforms: Databricks, Snowflake
• Data streaming systems: Kafka, Storm, Spark-Streaming, etc.
• Languages: Python, R, Scala, Go
• Ability to inspect existing data pipelines, discern their purpose and functionality, and re-implement them efficiently in Databricks.
• Advanced working SQL knowledge and experience working with relational databases
• Advanced working knowledge and of NoSQL databases
• Experience with message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Experience manipulating, processing, and extracting value from large, disconnected datasets.
• Experience manipulating structured and unstructured data for analysis.
• Experience with data modeling tools and processes.
• Experience aggregating and transforming data from multiple datasets to create data products
• Experience working in an Agile environment