Data Architect

Industry: Finance
Company size: 251-10K

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Job description

A fast-growing company helping real estate investors to realize the full potential of their real estate investment strategies is looking for a Data Architect. The selected candidate will help to create new products while collaborating with the Product, DevOps, and Data Science teams to explore different tools and processes. The US-based company offers funds to real estate investors to facilitate transactions, loans, and mortgage financing options. This is a great opportunity for developers to test their skills and build lucrative careers. 


Job Responsibilities:

  • Implement scalable processes for large-scale data processing
  • Develop robust data processing pipelines for various scenarios such as bulk Ingestion, real-time streaming applications, and ML processes
  • Develop data pipelines that provide low latency and are highly scalable in a complex environment
  • Collaborate with data scientists/product owners and be accountable for data processing needs from development to production
  • Evaluate and note down processes that improve data quality, data discoverability, data lineage, and data governance
  • Express technical and business risks to those concerned
  • Adapt to changing business conditions and new information quickly 
  • Actively influence the design and shape of the ML roadmap within this scope
  • Develop strong awareness of organizational health
  • Identify and make recommendations to solve complex issues
  • Deliver constructive feedback to team members 

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 4+ years of relevant experience as a software engineer
  • Demonstrated ability to ship complex large-scale data processing systems with low latency
  • Prolific experience with Azure Databricks
  • Demonstrable experience in building and developing ETL code in Python, PySpark, etc
  • Prior experience with SQL and NoSQL to process data, preferably in cloud databases such as Snowflake, Redshift, etc. 
  • Knowledge of data processing testing frameworks such as Great Expectations
  • Extensive experience working with Docker and Linux (preferably in Kubernetes)
  • Hands-on experience with data pipeline orchestration tools such as Airflow, Dagster, Prefect, etc.
  • Working experience in Agile and test-driven methodologies
  • Strong verbal and written communication skills
  • Analytical skills and passion for answering questions with data
  • Fluent in verbal and written English

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