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Job Title: Lead Data Engineer-Snowflake
Location: Bangalore/ Pune/Hyderabad
Job Information
Key Responsibilities:
• Lead the development and implementation of data pipelines and data models using Snowflake
and DBT.
• Design and optimize ETL workflows using Apache Airflow to ensure efficient data processing.
• Collaborate with cross-functional teams to gather requirements and translate them into technical
specifications.
• Perform data analysis and troubleshooting to ensure data integrity and reliability.
• Mentor and guide junior engineers, supporting their growth and development within the team.
• Stay current with industry trends and best practices related to data engineering and cloud
technologies.
Qualifications:
• Bachelor's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in data engineering or a related field, with a focus on Snowflake.
• Strong expertise in DBT, Airflow, and Python programming.
• Solid understanding of data warehousing concepts and best practices.
• Excellent problem-solving skills and the ability to work independently as well as part of a team.
• Strong communication and collaboration skills to work effectively with stakeholders at all levels.
Interested candidates can apply using this link- https://app.employlabs.ai/apply/Q7grmOB86K
Job ID: 153756117
Skills:
Amazon S3, Dimensional Modeling, Data Warehousing, Redshift, Python, Sql, ELT, Etl, AWS, Athena, Teradata
Skills:
snowflake , Cloudformation, Scala, Sql, ELT, Jenkins, Git, Gcp, Terraform, Databricks, Azure, Python, AWS, Azure DevOps, Etl
Skills:
snowflake , Java, Data Modelling, Apache Spark, Sql, Apache Airflow, Gcp, Databricks, Azure, Python, AWS, Data Warehousing principles, ETL processes
Skills:
data engineering , snowflake , S3, Unix, Sql, Cloudwatch, Qlik Replicate, Gitlab, Python, AWS, Step Function, Airflow, Snowpark, dbt, Glue
Skills:
S3, Data Factory, Data Modeling, Automated Testing, ELT, Azure Synapse, Python, AWS, Scala, Apache Spark, Redshift, Gcp, Databricks, Data Warehousing, DataFlow, Azure, Etl, Google BigQuery, Lakehouse Architectures, Unity Catalog, DataOps, ADLS, Glue, Delta Lake, Infrastructure-as-Code