Sr Data Engineer

Zyoin Group; Bengaluru; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

Zyoin Group in Bengaluru is hiring a Senior Data Engineer to join a fast-growing data organization building scalable data products that empower business teams to analyze subscriber movements, measure key metrics, and support revenue initiatives.

Responsibilities include designing scalable data models, ETL/ELT pipelines, data quality checks, and working with Snowflake/Redshift, Spark, Databricks, and Airflow.

Qualifications

• 5+ years of experience in Data Engineering
• Strong hands-on experience building data pipelines and data warehouse solutions
• Partner with stakeholders to understand data, reporting, and business requirements
• Design scalable and performant data models, including dimensional modeling and normalization
• Design and develop robust ETL/ELT pipelines and define data integration strategies
• Develop and maintain ETL workflows using orchestration tools such as Apache Airflow
• Build automated Data Quality checks to ensure data accuracy and reliability
• Work with relational databases and distributed data systems such as Snowflake or Amazon Redshift
• Perform advanced SQL and ETL performance tuning to optimize processing and queries
• Work with Python, PySpark, Spark, Databricks, or EMR for large-scale processing
• Implement database deployments and schema changes using tooling
• Build and report on business KPIs and metrics within data warehouses
• Perform ad hoc data analysis to support data-driven insights
• Participate in Agile/Scrum ceremonies and collaborate with teams
• Strong understanding of data modeling principles including dimensional modeling and normalization
• Strong SQL proficiency to analyze and optimize complex queries
• Strong analytical and problem-solving skills to translate requirements into scalable data solutions
• Excellent written and verbal communication skills

Responsibilities

• Build scalable data pipelines and data warehouse solutions.
• Collaborate with engineering, analytics, and business teams.
• Collect and integrate data from internal and external systems.
• Design scalable data models with dimensional modeling and normalization.
• Develop ETL/ELT pipelines and data integration strategies.
• Create and maintain ETL workflows with Apache Airflow.
• Establish automated data quality checks for reliability.
• Work with Snowflake or Redshift for data storage.
• Tune SQL and ETL performance for efficiency.
• Use Python, PySpark, Spark, Databricks, or EMR for processing.
• Handle schema changes and deployments with appropriate tools.
• Build and report on KPIs and metrics within warehousing environments.
• Perform ad hoc data analysis to support decisions.
• Engage in Agile ceremonies and cross-functional collaboration.
• Communicate complex data concepts clearly to non-technical stakeholders.

Skills

Data engineering

ETL pipelines

SQL

Python

PySpark

Spark

Databricks

Snowflake

Redshift

Airflow

Data modeling

Quality checks

Agile/Scrum

Communication

Tools

Airflow

Snowflake

Redshift

Databricks

Spark

Python

SQL

Job description

We are hiring for a Senior Data Engineer to join a fast-growing data organization building scalable data products that enable business teams to analyze subscriber movements, measure key business metrics, and support revenue generation initiatives.

Work on large-scale data engineering problems involving data modeling, ETL pipelines, data warehousing, orchestration, and performance optimization. You'll collaborate with engineering, analytics, infrastructure, and business teams to build scalable data solutions that directly support business decision-making and revenue initiatives.

Roles and Responsibilities:

• 5+ years of experience in Data Engineering with strong hands-on experience building data pipelines and data warehouse solutions.
• Partner with technical and non-technical stakeholders to understand data, reporting, and business requirements.
• Work with engineering teams to collect and integrate data from internal and external systems.
• Design scalable and performant data models, including dimensional modeling and database normalization.
• Design and develop robust ETL/ELT pipelines and define appropriate data integration strategies.
• Develop and maintain ETL workflows using orchestration tools such as Apache Airflow.
• Build and implement automated Data Quality checks to ensure accuracy, consistency, and reliability of data.
• Work with relational databases and distributed data systems such as Snowflake or Amazon Redshift.
• Perform advanced SQL and ETL performance tuning to optimize data processing and query performance.
• Work with technologies such as Python, PySpark, Spark, Databricks, or EMR for large-scale data processing.
• Implement database deployments and schema changes using tools such as Schema Change.
• Build and report on business KPIs and metrics within data warehousing environments.
• Perform ad hoc data analysis and support business teams with data-driven insights.
• Participate in Agile/Scrum ceremonies and collaborate closely with cross-functional engineering and analytics teams.
• Strong understanding of data modeling principles, including dimensional modeling and normalization.
• Strong SQL expertise with the ability to analyze and optimize complex queries and data workloads.
• Strong analytical and problem-solving skills with the ability to translate business requirements into scalable data solutions.
• Excellent written and verbal communication skills.