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Data Engineer
Intellikart Ventures LLP's logo

Data Engineer

2 - 5 yrs
₹9L - ₹15L / yr
Pune
Skills
PowerBI
SQL
ETL
snowflake
Apache Kafka
Data engineering

Experience: 4+ years.

Location: Vadodara & Pune

Skills Set- Snowflake, Power Bi, ETL, SQL, Data Pipelines

What you'll be doing:

  • Develop, implement, and manage scalable Snowflake data warehouse solutions using advanced features such as materialized views, task automation, and clustering.
  • Design and build real-time data pipelines from Kafka and other sources into Snowflake using Kafka Connect, Snowpipe, or custom solutions for streaming data ingestion.
  • Create and optimize ETL/ELT workflows using tools like DBT, Airflow, or cloud-native solutions to ensure efficient data processing and transformation.
  • Tune query performance, warehouse sizing, and pipeline efficiency by utilizing Snowflakes Query Profiling, Resource Monitors, and other diagnostic tools.
  • Work closely with architects, data analysts, and data scientists to translate complex business requirements into scalable technical solutions.
  • Enforce data governance and security standards, including data masking, encryption, and RBAC, to meet organizational compliance requirements.
  • Continuously monitor data pipelines, address performance bottlenecks, and troubleshoot issues using monitoring frameworks such as Prometheus, Grafana, or Snowflake-native tools.
  • Provide technical leadership, guidance, and code reviews for junior engineers, ensuring best practices in Snowflake and Kafka development are followed.
  • Research emerging tools, frameworks, and methodologies in data engineering and integrate relevant technologies into the data stack.


What you need:

Basic Skills:


  • 3+ years of hands-on experience with Snowflake data platform, including data modeling, performance tuning, and optimization.
  • Strong experience with Apache Kafka for stream processing and real-time data integration.
  • Proficiency in SQL and ETL/ELT processes.
  • Solid understanding of cloud platforms such as AWS, Azure, or Google Cloud.
  • Experience with scripting languages like Python, Shell, or similar for automation and data integration tasks.
  • Familiarity with tools like dbt, Airflow, or similar orchestration platforms.
  • Knowledge of data governance, security, and compliance best practices.
  • Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues.
  • Ability to work in a collaborative team environment and communicate effectively with cross-functional teams


Responsibilities:

  • Design, develop, and maintain Snowflake data warehouse solutions, leveraging advanced Snowflake features like clustering, partitioning, materialized views, and time travel to optimize performance, scalability, and data reliability.
  • Architect and optimize ETL/ELT pipelines using tools such as Apache Airflow, DBT, or custom scripts, to ingest, transform, and load data into Snowflake from sources like Apache Kafka and other streaming/batch platforms.
  • Work in collaboration with data architects, analysts, and data scientists to gather and translate complex business requirements into robust, scalable technical designs and implementations.
  • Design and implement Apache Kafka-based real-time messaging systems to efficiently stream structured and semi-structured data into Snowflake, using Kafka Connect, KSQL, and Snow pipe for real-time ingestion.
  • Monitor and resolve performance bottlenecks in queries, pipelines, and warehouse configurations using tools like Query Profile, Resource Monitors, and Task Performance Views.
  • Implement automated data validation frameworks to ensure high-quality, reliable data throughout the ingestion and transformation lifecycle.
  • Pipeline Monitoring and Optimization: Deploy and maintain pipeline monitoring solutions using Prometheus, Grafana, or cloud-native tools, ensuring efficient data flow, scalability, and cost-effective operations.
  • Implement and enforce data governance policies, including role-based access control (RBAC), data masking, and auditing to meet compliance standards and safeguard sensitive information.
  • Provide hands-on technical mentorship to junior data engineers, ensuring adherence to coding standards, design principles, and best practices in Snowflake, Kafka, and cloud data engineering.
  • Stay current with advancements in Snowflake, Kafka, cloud services (AWS, Azure, GCP), and data engineering trends, and proactively apply new tools and methodologies to enhance the data platform. 


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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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