Data Engineer

Kanerika Inc; Hyderabad; On-site; INR 1,000,000 - 1,800,000; Full time

Job summary

Kanerika Inc in Hyderabad is seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines using Databricks, Microsoft Fabric, or Snowflake, and to enable effective data visualization with Power BI for business stakeholders.

You will work with cross‑functional teams to define data requirements, governance standards, and best practices, ensure data quality and security, and automate CI/CD workflows for data solutions while monitoring pipelines and dashboards for

Qualifications

• Bachelor’s or Master’s degree in CS/IT/Engineering or related field.
• Proven Data Engineer with Databricks or Fabric or Snowflake expertise.
• Hands-on Power BI (data modeling, DAX, dashboards, performance).
• Strong SQL and at least one programming language (Python/Scala/Java).
• Experience building scalable pipelines in cloud environments (Azure/AWS/GCP).
• Knowledge of data ecosystems across major cloud providers.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines using Databricks, Fabric, or Snowflake.
• Build and optimize data workflows for performance, scalability, and cost efficiency in cloud environments (Azure/AWS/GCP).
• Implement and manage data lakes, data warehouses, or lakehouse architectures.
• Develop and maintain Power BI dashboards and reports to support business insights and decision-making.
• Collaborate with cross-functional teams to define data requirements, governance standards, and best practices.
• Ensure data quality, integrity, and security across all platforms.
• Automate workflows and support CI/CD deployments for data solutions.
• Monitor and troubleshoot pipelines and dashboards to ensure high availability and reliability.

Education

Bachelor’s/Master’s degree in Computer Science, Information Technology, Engineering, or related field

Tools

Databricks

Microsoft Fabric

Snowflake

Power BI

SQL

Python

Scala

Java

Azure

AWS

GCP

Job description

We are seeking a skilled Data Engineer with strong experience in Databricks, Microsoft Fabric, or Snowflake, along with Power BI expertise, to design, build, and optimize scalable data pipelines and analytics solutions. You will also play a key role in enabling effective data visualization and reporting for business stakeholders.

Key Responsibilities

• Design, develop, and maintain ETL/ELT pipelines using Databricks, Fabric, or Snowflake.
• Build and optimize data workflows for performance, scalability, and cost efficiency in cloud environments (Azure/AWS/GCP).
• Implement and manage data lakes, data warehouses, or lakehouse architectures.
• Develop and maintain Power BI dashboards and reports to support business insights and decision-making.
• Collaborate with cross-functional teams to define data requirements, governance standards, and best practices.
• Ensure data quality, integrity, and security across all platforms.
• Automate workflows and support CI/CD deployments for data solutions.
• Monitor and troubleshoot pipelines and dashboards to ensure high availability and reliability.

Required Qualifications

• Bachelor’s/Master’s degree in Computer Science, Information Technology, Engineering, or related field.
• Proven experience as a Data Engineer with expertise in Databricks OR Fabric OR Snowflake.
• Hands‑on experience with Power BI (data modeling, DAX, dashboard creation, performance optimization).
• Strong proficiency in SQL and at least one programming language (Python/Scala/Java).
• Experience with data modeling and building scalable pipelines in cloud environments.
• Knowledge of Azure, AWS, or GCP and their data ecosystem.
• Strong problem‑solving, analytical, and communication skills.

Preferred Qualifications

• Experience with streaming data technologies (Kafka, Event Hubs, Kinesis).
• Knowledge of Delta Lake, Synapse, or Snowflake performance optimization.
• Familiarity with DevOps practices for data (CI/CD, Git, Infrastructure as Code).
• Exposure to machine learning pipelines or advanced analytics.
• Understanding of data governance, lineage, and compliance frameworks