Hadoop Developer - Fulltime

Title: Hadoop developer

Location:  Addison, TX – Onsite (Relocation Works)

Duration: Fulltime

Video Interviews

SUBMISSION REQUIREMENTS:

Need Genuine LinkedIn- NO RECENT OR MULTIPLE LINKEDIN

Must have full educational details with University Name and year of completion in resume.

WITHOUT ABOVE MENTIONED PREREQUISITE RESUME WILL BE DEEMED AS FAKE.

Job Description:  

 Exp- 5 to 8 years

Roles & Responsibilities

• 3–5+ years of experience in Data Engineering, Software Engineering, or related technical discipline.
• Strong proficiency in Python, and SQL for advanced data transformations.
• Hands-on experience designing and building ETL/ELT pipelines, data ingestion processes, and distributed data processing jobs.
• Practical experience working with distributed data tools such as Apache Spark, Databricks, or Hadoop ecosystems.
• Experience building and managing datasets in relational and/or cloud‑based data platforms (Teradata, Snowflake, SQL Server, Azure/AWS/Google Cloud Platform).
• Solid understanding of data modeling, metadata, data quality controls, data lineage, and secure data management.
• Experience contributing to automated test suites, analyzing test failures, and supporting test-driven development.
• Knowledge of CI/CD pipelines, version control (Git), and automated deployment practices.
• Experience adhering to enterprise data governance, compliance, and operational risk frameworks.
• Ability to troubleshoot pipeline issues, performance bottlenecks, and data discrepancies.
• Strong communication skills and ability to collaborate across engineering, product, and business teams.
• Experience implementing monitoring and observability for data pipelines (logs, metrics, health checks).
• Advanced experience with performance tuning of SQL, Spark, or distributed data workflows.
• Knowledge of data security practices (encryption, masking, PII handling).
• Experience supporting analytical workloads, BI tools, or data science teams.
• Prior experience in a financial institution or other regulated industry
•  
• A Data Engineer is essential to implement efficient data flows, enforce data management standards, enhance data quality, and support continuous delivery and release cycles. Without this role, the project risks delays in data readiness, gaps in data compliance, reduced quality of analytical outputs, and inability to support downstream systems effectively.