Job Title: Data Engineer
Location: Open to candidates located in
Utah, Ohio, Arizona, Nebraska, Missouri, Louisiana, New Mexico, Tennessee, Alabama, North Dakota, South Dakota, Montana, Kansas, Oklahoma, Mississippi, Arkansas, Iowa, Indiana, Kentucky, Vermont, West Virginia
Location : Remote/ (with occasional travel if required)
Work Authorization: OPT / W2
Please Find the Below Requirement If You're Interested, Please Share Me your Updated Resume To rakeshmanda@adroitinnovative.com
Position Summary:
We are seeking a Data Engineer with strong experience in Azure Databricks, Delta Lake, and Snowflake to help build robust, scalable, and optimized data pipelines that support analytics and LLM-based applications. The ideal candidate will be a strong problem solver who can translate complex business logic into structured, curated datasets and troubleshoot data quality and performance issues.
Key Responsibilities:
Design and develop scalable data pipelines and ETL processes using Azure Databricks and Delta Lake.
Build and maintain curated datasets that support analytical and LLM-driven use cases.
Convert business KPIs and complex metrics into structured, high-quality datasets.
Implement data quality checks, profiling, validation, and observability measures.
Optimize and troubleshoot slow-running pipelines and resolve data quality issues.
Collaborate with stakeholders including data scientists, analysts, and business teams to gather requirements.
Create and maintain documentation around workflows, schemas, and transformation logic.
Work across multiple data warehouse platforms including Snowflake, Azure, and Databricks.
Qualifications:
5 6 years of hands-on data engineering experience.
Strong expertise in Azure Databricks, Delta Lake, and Azure Data Factory.
Hands-on experience in Snowflake and understanding of its architecture and differences from traditional data warehouses.
Proficient in SQL and Python for data transformation and scripting.
Solid understanding of data modeling concepts - especially for analytical and LLM-ready datasets.
Familiarity with CI/CD pipelines, notebook organization, dependency management, and job orchestration in Databricks.
Experience identifying and resolving data issues in production pipelines
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