Background: Boutique Advisory firm specializing in cutting edge Litigation and Risk Analytics is looking to augment its Data Science practice by bringing in a Principal Data Engineer. Principal Data Engineer will build out a best-in-class data ingestion practice for the organization and optimize data processing and its transformation. Data Engineers’ data wrangling skills will enable Data Scientists to perform Analytics in a more optimal and efficient manner that will add great value to Litigation and Risk initiatives.


What Will the Principal Data Engineer Do:

  • be absolutely hands-on and provide strategic support on best practices with regards to data: ingestion, processing, transformation, and integration strategies within its cloud data environment
  • help build cloud infrastructure and architecture for collecting, storing, processing, and analyzing big data in batch and streaming pipelines
  • develop, manage, and automate ETL processes and data pipelines to efficiently ingest data
  • lead operational efforts to make the lives of Data Scientists easier by cleansing and aggregating data including productionalizing machine learning algorithms and BI reports
  • provide general guidance on data management, data warehousing, data modeling, data governance, data security, and cloud infrastructure initiatives
  • lead the evaluation, implementation, and deployment of emerging tools and process for data engineering within a Data Science and Analytics environment


More Info – Principal Data Engineer Role:

  • full-time role + great benefits
  • hybrid work environment (onsite + remote). They have offices in the following locations: Austin, Boston, Chicago, Dallas, Denver, Houston, Los Angeles, Miami, New York, Palo Alto, San Francisco, Washington, DC. Figure you will be in the office 2 – 3 times per week and rest will be remote
  • comfortable being the senior most Data Engineer within Analytics practice with one other Data Engineer



  • experience as a Data Engineer with strong data ingestion skills i.e.: ETL, automation of data pipelines, batch / stream processing
  • exposure to leading cloud platforms is a HUGE plus: Azure, AWS, GCP
  • following tools / stacks are desired: SQL, Python, Spark, understanding of Snowflake, Databricks, Redshift, BigQuery

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