Senior Data Engineer

3 weeks ago

Hyderabad, India Unify Technologies Full time

Company Description

Unify Technologies is a leading digital engineering company committed to helping global clients build high-quality software products quickly and affordably. With extensive experience in software product engineering practices, Unify Technologies delivers custom software solutions. We collaborate with industry leaders across multiple geographies to drive innovation and efficiency.

Role Description

This is a full-time, on-site role for a Senior Data Engineer, located in Hyderabad. The Senior Data Engineer will be responsible for designing, developing, and maintaining data pipelines and databases. The role includes data modeling, ETL processes, and ensuring data architecture meets industry standards. The Senior Data Engineer will collaborate with cross-functional teams to support data analytics and business intelligence initiatives.

Key Qualifications:

  • 5 Yrs of experience in software in a Data Engineering role
  • Experience in Snowflake (3+ Yrs) Including performance tuning and data modeling
  • Experience with relational database and managing structured data at scale
  • Strong SQL skills with the ability to write, Optimize, analyze and debug complex queries
  • Experience with Data Orchestration and ETL tools, specifically Airflow and DBT in a production environment
  • Proficiency in Python for Airflow DAGs and general Data manipulation and automation tasks.
  • Ability to diagnose and resolve data quality Issues and performance bottlenecks
  • Knowledge of Data warehouse, data lake and data pipeline performance tuning and troubleshooting.

Roles & Responsibilities:

  • Design, implement, and maintain robust data pipelines for data ingress and orchestration workflows
  • Develop and enforce standards for data warehousing, data ingress/egress, and production data set quality
  • Collaborate with engineering, product, and analytics teams to define and deliver on data requirements
  • Monitor, troubleshoot, and resolve performance issues and bottlenecks across data pipelines, data lakes, and warehouses.
  • Other data related tasks & duties, as assigned.

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