Data Engineer - United States

manipulate data from multiple sources.

· Automate data workflows such as data ingestion, aggregation, and ETL processing.

· Prepare raw data in Data Warehouses into a consumable dataset for both technical and non-technical stakeholders.

· Partner with data scientists and functional leaders in sales, marketing, and product to deploy machine learning models in production.

· Build, maintain, and deploy data products for analytics and data science teams on cloud platforms (e.g. AWS, Azure, GCP).

· Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures.

· Monitor data systems performance and implement optimization strategies.

· Leverage data controls to maintain data privacy, security, compliance, and quality for allocated areas of ownership.

You have what it takes if you have...

· 3+ years of SQL skills and experience with relational databases and database design.

· Experience working with cloud Data Warehouse solutions - Databricks, Apache Spark

· Experience working with data ingestion tools such as Fivetran, stitch, or Matillion.

· Working knowledge of Cloud-based solutions (e.g. AWS, Azure, GCP).

· Experience building and deploying machine learning models in production.

· Strong proficiency in object-oriented languages: Python, Java, C++, Scala.

· Strong proficiency in scripting languages like Bash.

· Strong proficiency in data pipeline and workflow management tools (e.g., Airflow).

· Strong project management and organizational skills.

· Excellent problem-solving, communication, and organizational skills.

· Proven ability to work independently and with a team.

Extra dose of awesome if you have...

· Good understanding of NoSQL databases like CrateDB, Redis, Cassandra, MongoDB, or Neo4j.

· Experience with working on large data sets and distributed computing (e.g. Hive/Hadoop/Spark/Presto/MapReduce).