Senior Data Engineer

HCLTech; Hyderabad, Pune District, Bengaluru; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

HCLTech in Hyderabad seeks a senior data engineer to design and manage scalable data pipelines and data models.

You will own data quality, performance optimization, and collaboration with backend teams, leveraging Snowflake/Databricks and orchestration tools like Dagster or Airflow.

Qualifications

• 7+ years of experience in data engineering.
• Strong SQL expertise and complex query optimization.
• Experience building ETL/ELT pipelines.
• Exposure to data modeling concepts.
• Experience with Redshift, Snowflake and/or Databricks.
• Orchestration tools like Dagster or Airflow.
• Python for data processing and data quality ownership.
• Ability to optimize large-scale data workloads.

Responsibilities

• Build and maintain scalable ETL/ELT data pipelines.
• Own data modeling, transformations, and data quality processes.
• Optimize query performance and data workload efficiency.
• Collaborate with backend teams to support data requirements.
• Ensure reliability and integrity of data systems.
• Independently manage and improve data systems.

Skills

Snowflake

Databricks

ETL/ELT

SQL

Dagster

Airflow

Python

Data modeling

Data quality

Tools

Redshift

Snowflake

Databricks

Job description

Experience: 7+ Yrs

Skill: Snowflake or Databricks, ETL, SQL, Dagster , Airflow

• 7 years of experience in data engineering
• Strong SQL expertise (complex queries, optimization, performance tuning)
• Experience building ETL/ELT pipelines
• Good understanding of data modeling concepts
• Experience with Redshift, Snowflake and/or Databricks
• Exposure to orchestration tools like Dagster or Airflow
• Python for data processing
• Strong ownership of data quality and pipeline reliability
• Experience optimizing large-scale data workloads
• Ability to independently manage and improve data systems
• Build and maintain scalable data pipelines (ETL/ELT)
• Own data modeling, transformations, and data quality processes
• Optimize query performance and improve efficiency of data workloads
• Work closely with backend teams to support data requirements
• Ensure reliability and integrity of data systems