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Senior Data Engineers
3 months ago
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We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long term project. Here are a few details.
Role: Senior Data Engineers
Location: Hyderabad, Bangalore, Pune
Hybrid Mode Position
Exp: 7 - 12 Years
Requirements
We are seeking an experienced Senior Data Engineer with over 7 years of expertise in architecting, designing, and building data engineering solutions and data platforms. The ideal candidate will have a strong background in developing data warehouses and platforms using technologies such as Redshift and Snowflake, and experience with data transformation tools, distributed data processing frameworks, and real-time data stream processing. Proficiency in AWS services, advanced SQL programming, and dimensional modeling is essential. The role requires excellent communication, collaboration, analytical, and problem-solving skills.
Key Responsibilities:
- Data Platform Architecture: Architect, design, and build data engineering solutions and platforms, including data warehouses and data platforms using Redshift or Snowflake.
- Data Acquisition and Transformation: Utilize data acquisition and transformation tools such as Fivetran and DBT to streamline data integration and processing.
- Pipeline Optimization: Develop and maintain highly optimized and efficient data engineering pipelines using Python and PySpark.
- Distributed Processing: Work with distributed data processing frameworks like Apache Hadoop, Apache Spark, or Apache Flink.
- Real-Time Data Processing: Implement real-time data stream processing using Apache Kafka, Kinesis, or Flink.
- AWS Services: Utilize various AWS services including S3, EC2, EMR, Lambda, RDS, DynamoDB, Redshift, and Glue Catalog for data management and processing.
- SQL Programming: Apply expertise in advanced SQL programming and SQL performance tuning to ensure efficient data querying and processing.
- Version Control: Use version control tools such as GitHub or Bitbucket to manage and track code changes.
- Dimensional Modeling: Demonstrate expert-level understanding of dimensional modeling techniques for data warehousing and business intelligence.
- Communication and Collaboration: Work collaboratively with cross-functional teams, displaying excellent communication and adaptability.
- Analytical Skills: Apply strong analytical skills with attention to detail, focusing on accuracy, consistency, and quality.
- Problem-Solving: Utilize strong logical and problem-solving skills with critical thinking to address complex data engineering challenges.
Qualifications:
- 7+ years of experience in data engineering, including architecting, designing, and building data engineering solutions and platforms.
- Experience in building data warehouses/data platforms on Redshift or Snowflake.
- Experience with data acquisition and transformation tools such as Fivetran and DBT.
- Experience in building optimized and efficient data engineering pipelines using Python and PySpark.
- Experience with distributed data processing frameworks like Apache Hadoop, Apache Spark, or Apache Flink.
- Experience with real-time data stream processing using Apache Kafka, Kinesis, or Flink.
- Experience with AWS services (S3, EC2, EMR, Lambda, RDS, DynamoDB, Redshift, Glue Catalog).
- Expertise in advanced SQL programming and SQL performance tuning.
- Experience with version control tools such as GitHub or Bitbucket.
- Expert-level understanding of dimensional modeling techniques.
- Excellent communication, adaptability, and collaboration skills.
- Strong analytical skills, attention to detail, and problem-solving abilities.
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