Senior Data Engineer- Snowflake
Job Title: Data Engineer<\/b><\/span>
<\/h3><\/p>
Experience:<\/b> 7+ Years
<\/div> Location:<\/b> Chennai<\/span><\/span> (On\-site)
<\/div> Employment Type:<\/b> Full\-time
<\/div><\/p>
Role Overview<\/b><\/span>
<\/h3>We are looking for an experienced Data Engineer<\/b> to build, optimize, and manage scalable data pipelines and architectures. The ideal candidate will have strong expertise in modern data platforms, with hands\-on experience in Snowflake<\/b> and cloud\-based data solutions.
<\/p>
Key Responsibilities<\/b><\/span>
<\/h3>- Design, build, and maintain scalable data pipelines and ETL/ELT processes
<\/li> - Develop and optimize data models and data warehouse solutions
<\/li> - Work extensively with Snowflake<\/b> for data storage, transformation, and performance tuning
<\/li>- Collaborate with BI, analytics, and product teams to deliver clean and reliable datasets
<\/li> - Ensure data quality, integrity, and governance across systems
<\/li> - Optimize query performance and cost efficiency in Snowflake
<\/li> - Integrate data from multiple sources (APIs, databases, third\-party systems)
<\/li> - Implement data security and access controls
<\/li><\/ul>
<\/span>
Requirements<\/h3>Required Skills & Qualifications<\/b><\/span>
<\/h3>- 7+ years of experience in Data Engineering or related roles
<\/li> - Strong expertise in Snowflake<\/b> (data modeling, performance tuning, optimization)
<\/li>- Advanced SQL skills and experience with large\-scale data processing
<\/li> - Hands\-on experience with ETL/ELT tools (e.g., Airflow, Informatica, dbt, or similar)
<\/li> - Experience with cloud platforms such as AWS / Azure / GCP
<\/li> - Strong understanding of data warehousing concepts (star schema, snowflake schema, etc.)
<\/li> - Experience with Python or Scala for data processing
<\/li> - Knowledge of data pipeline orchestration and scheduling
<\/li><\/ul>
<\/div><\/span>
Benefits<\/h3>Preferred Skills<\/b><\/span>
<\/h3>- Experience with big data technologies (Spark, Hadoop)
<\/li> - Familiarity with streaming tools (Kafka, Kinesis)
<\/li> - Experience with CI/CD pipelines and DevOps practices
<\/li> - Exposure to data governance and data security best practices
<\/li><\/ul>
Key Competencies<\/b><\/span>
<\/h3>- Strong problem\-solving and analytical skills
<\/li> - Ability to work with cross\-functional teams
<\/li> - Good communication and stakeholder management
<\/li> - High ownership and accountability
<\/li><\/ul>
<\/div><\/span>
<\/div>
<\/div>
<\/div>
<\/p>
Role Overview<\/b><\/span>
<\/h3>We are looking for an experienced Data Engineer<\/b> to build, optimize, and manage scalable data pipelines and architectures. The ideal candidate will have strong expertise in modern data platforms, with hands\-on experience in Snowflake<\/b> and cloud\-based data solutions.
<\/p>
Key Responsibilities<\/b><\/span>
<\/h3>- Design, build, and maintain scalable data pipelines and ETL/ELT processes
<\/li> - Develop and optimize data models and data warehouse solutions
<\/li> - Work extensively with Snowflake<\/b> for data storage, transformation, and performance tuning
<\/li>- Collaborate with BI, analytics, and product teams to deliver clean and reliable datasets
<\/li> - Ensure data quality, integrity, and governance across systems
<\/li> - Optimize query performance and cost efficiency in Snowflake
<\/li> - Integrate data from multiple sources (APIs, databases, third\-party systems)
<\/li> - Implement data security and access controls
<\/li><\/ul>
<\/span>
Requirements<\/h3>Required Skills & Qualifications<\/b><\/span>
<\/h3>- 7+ years of experience in Data Engineering or related roles
<\/li> - Strong expertise in Snowflake<\/b> (data modeling, performance tuning, optimization)
<\/li>- Advanced SQL skills and experience with large\-scale data processing
<\/li> - Hands\-on experience with ETL/ELT tools (e.g., Airflow, Informatica, dbt, or similar)
<\/li> - Experience with cloud platforms such as AWS / Azure / GCP
<\/li> - Strong understanding of data warehousing concepts (star schema, snowflake schema, etc.)
<\/li> - Experience with Python or Scala for data processing
<\/li> - Knowledge of data pipeline orchestration and scheduling
<\/li><\/ul>
<\/div><\/span>
Benefits<\/h3>Preferred Skills<\/b><\/span>
<\/h3>- Experience with big data technologies (Spark, Hadoop)
<\/li> - Familiarity with streaming tools (Kafka, Kinesis)
<\/li> - Experience with CI/CD pipelines and DevOps practices
<\/li> - Exposure to data governance and data security best practices
<\/li><\/ul>
Key Competencies<\/b><\/span>
<\/h3>- Strong problem\-solving and analytical skills
<\/li> - Ability to work with cross\-functional teams
<\/li> - Good communication and stakeholder management
<\/li> - High ownership and accountability
<\/li><\/ul>
<\/div><\/span>
<\/p>
Key Responsibilities<\/b><\/span>
<\/h3>- Design, build, and maintain scalable data pipelines and ETL/ELT processes
<\/li> - Develop and optimize data models and data warehouse solutions
<\/li> - Work extensively with Snowflake<\/b> for data storage, transformation, and performance tuning
<\/li>- Collaborate with BI, analytics, and product teams to deliver clean and reliable datasets
<\/li> - Ensure data quality, integrity, and governance across systems
<\/li> - Optimize query performance and cost efficiency in Snowflake
<\/li> - Integrate data from multiple sources (APIs, databases, third\-party systems)
<\/li> - Implement data security and access controls
<\/li><\/ul>
<\/span>
Requirements<\/h3>Required Skills & Qualifications<\/b><\/span>
<\/h3>- 7+ years of experience in Data Engineering or related roles
<\/li> - Strong expertise in Snowflake<\/b> (data modeling, performance tuning, optimization)
<\/li>- Advanced SQL skills and experience with large\-scale data processing
<\/li> - Hands\-on experience with ETL/ELT tools (e.g., Airflow, Informatica, dbt, or similar)
<\/li> - Experience with cloud platforms such as AWS / Azure / GCP
<\/li> - Strong understanding of data warehousing concepts (star schema, snowflake schema, etc.)
<\/li> - Experience with Python or Scala for data processing
<\/li> - Knowledge of data pipeline orchestration and scheduling
<\/li><\/ul>
<\/div><\/span>
Benefits<\/h3>Preferred Skills<\/b><\/span>
<\/h3>- Experience with big data technologies (Spark, Hadoop)
<\/li> - Familiarity with streaming tools (Kafka, Kinesis)
<\/li> - Experience with CI/CD pipelines and DevOps practices
<\/li> - Exposure to data governance and data security best practices
<\/li><\/ul>
Key Competencies<\/b><\/span>
<\/h3>- Strong problem\-solving and analytical skills
<\/li> - Ability to work with cross\-functional teams
<\/li> - Good communication and stakeholder management
<\/li> - High ownership and accountability
<\/li><\/ul>
<\/div><\/span>
<\/li>
<\/li>
<\/li>
<\/li>
<\/li>
<\/li>
<\/li>
<\/li><\/ul>
<\/span>
Requirements<\/h3>Required Skills & Qualifications<\/b><\/span>
<\/h3>- 7+ years of experience in Data Engineering or related roles
<\/li> - Strong expertise in Snowflake<\/b> (data modeling, performance tuning, optimization)
<\/li>- Advanced SQL skills and experience with large\-scale data processing
<\/li> - Hands\-on experience with ETL/ELT tools (e.g., Airflow, Informatica, dbt, or similar)
<\/li> - Experience with cloud platforms such as AWS / Azure / GCP
<\/li> - Strong understanding of data warehousing concepts (star schema, snowflake schema, etc.)
<\/li> - Experience with Python or Scala for data processing
<\/li> - Knowledge of data pipeline orchestration and scheduling
<\/li><\/ul>
<\/div><\/span>
Benefits<\/h3>Preferred Skills<\/b><\/span>
<\/h3>- Experience with big data technologies (Spark, Hadoop)
<\/li> - Familiarity with streaming tools (Kafka, Kinesis)
<\/li> - Experience with CI/CD pipelines and DevOps practices
<\/li> - Exposure to data governance and data security best practices
<\/li><\/ul>
Key Competencies<\/b><\/span>
<\/h3>- Strong problem\-solving and analytical skills
<\/li> - Ability to work with cross\-functional teams
<\/li> - Good communication and stakeholder management
<\/li> - High ownership and accountability
<\/li><\/ul>
<\/div><\/span>
<\/h3>
- 7+ years of experience in Data Engineering or related roles
<\/li> - Strong expertise in Snowflake<\/b> (data modeling, performance tuning, optimization)
<\/li>- Advanced SQL skills and experience with large\-scale data processing
<\/li>- Hands\-on experience with ETL/ELT tools (e.g., Airflow, Informatica, dbt, or similar)
<\/li>- Experience with cloud platforms such as AWS / Azure / GCP
<\/li>- Strong understanding of data warehousing concepts (star schema, snowflake schema, etc.)
<\/li>- Experience with Python or Scala for data processing
<\/li>- Knowledge of data pipeline orchestration and scheduling
<\/li><\/ul>
<\/div><\/span>Benefits<\/h3>
Preferred Skills<\/b><\/span>
<\/h3>- Experience with big data technologies (Spark, Hadoop)
<\/li> - Familiarity with streaming tools (Kafka, Kinesis)
<\/li> - Experience with CI/CD pipelines and DevOps practices
<\/li> - Exposure to data governance and data security best practices
<\/li><\/ul>Key Competencies<\/b><\/span>
<\/h3>- Strong problem\-solving and analytical skills
<\/li> - Ability to work with cross\-functional teams
<\/li> - Good communication and stakeholder management
<\/li> - High ownership and accountability
<\/li><\/ul>
<\/div><\/span>
- Strong problem\-solving and analytical skills
- Advanced SQL skills and experience with large\-scale data processing