Offer summary

Qualifications:

Strong experience with Databricks, including Unity Catalog and Delta Lake file formats., Solid understanding of Microsoft Azure Analytics., Intermediate knowledge of Power BI is required., Experience with data ingestion and processing in cloud environments..

Key responsibilities:

Design and build scalable infrastructure for processing education data in a cloud-based environment.

Provide input on schema design for reporting and analytical needs.

Support development teams with database requirements for new features.

Build ETL/ELT solutions for data ingestion, transformation, and model monitoring.

Job description

Svitla Systems Inc. is looking for a Middle Data Engineer for a full-time position (40 hours per week) in Argentina. Our client is a market leader in higher education marketing, enrollment management, and student success coaching. They deliver marketing and related enrollment/student engagement support services for online and adult-focused college programs and partner with private lenders who provide student loans. The firm’s multi-channel services include search engine optimization (SEO), digital marketing, Over-the-Top (OTT) marketing, awareness media, and creative services. It provides coaching services for prospective students and student success. The company manages multiple inquiry-generation websites and conducts primary and secondary research on behalf of clients. The company aims to help connect students with schools that fit them. It was established in 2005 and is headquartered in New Jersey.

You will work daily in Databricks using SQL and Python, within the Microsoft Azure cloud environment, and Power BI is also part of the toolset.

Requirements

Strong experience with Databricks, including Unity Catalog, Parquet, and Delta Lake file formats, and Data Lake Medallion Architecture
Solid understanding of working with Microsoft Azure Analytics.
At least intermediate knowledge of Power BI.

Responsibilities

Design and build scalable infrastructure and platform to ingest, store, and process substantial amounts of education data (structured, semi-structured, and unstructured), including streaming and real-time into a cloud-based infrastructure.
Provide input on schema design for future reporting/analytical considerations.
Support to development teams with database needs for new features/products.
Build ETL/ELT-based solutions for effective data ingestion, transformation, data pipelines, model deployment, and model monitoring. This includes end-to-end data orchestration, layering, governance, metadata management, and cataloging.

We offer