Data Engineer Developer for Scalable Data Solutions
2 days ago
About ANSR: A Leading Life Science Tools and Integrated Systems Provider
At ANSR, we are dedicated to making genomics useful for all. Our global hub in Bengaluru focuses on technology activities that will help usher in the next wave of innovation in healthcare and medical research. If you're eager to work on challenging projects that use cutting-edge technology to transform the future of healthcare, this is your chance to join a truly remarkable team.
We are seeking an experienced Data Engineer Developer with 3-5 years of experience to join our talented team in Bangalore. In this role, you will be responsible for designing, implementing, and optimizing data pipelines, ETL processes, and data integration solutions using Python, Spark, SQL, Snowflake, dbt, and other relevant technologies.
Key Responsibilities:
- Data Pipeline Development: Design, develop, and maintain scalable and efficient data pipelines, ETL processes, and data integration solutions using Python, Spark, SQL, Snowflake, and other relevant technologies.
- Big Data Processing: Utilize big data processing frameworks such as Apache Spark to process and analyze large volumes of data efficiently.
- Data Transformations: Implement data transformations, aggregations, and business logic to support analytics and reporting requirements.
- Cloud-Based Data Platforms: Leverage cloud-based data platforms such as Snowflake to store and manage structured and semi--structured data at scale.
- Data Modeling and Documentation: Utilize dbt (Data Build Tool) for data modeling, transformation, and documentation to ensure data consistency, quality, and integrity.
- Performance Optimization: Monitor and optimize data pipelines and ETL processes for performance, scalability, and reliability.
- Data Quality and Integrity: Conduct data profiling, cleansing, and validation to ensure data quality and integrity across different data sets.
- Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver actionable insights.
- Professional Development: Stay updated on emerging technologies and best practices in data engineering, contributing to continuous improvement and innovation within the team.
Required Skills and Qualifications:
- Domain Knowledge: Global operations, manufacturing, supply chain data pipeline and KPI development domain knowledge is required.
- Education: Bachelor's degree in Computer Science, Engineering, or related field.
- Experience: 3-5 years of experience in data engineering, with proficiency in Python, Spark, SQL, Snowflake, dbt, and other relevant technologies.
- Distributed Computing: Strong understanding of distributed computing principles and big data processing frameworks such as Apache Spark.
- Cloud-Based Data Platforms: Hands-on experience with cloud-based data platforms such as Snowflake, AWS, Azure, or Google Cloud Platform.
- Data Integration: Experience with data modeling, ETL development, and data integration using SQL and Python.
- dbt (Data Build Tool): Familiarity with dbt (Data Build Tool) for managing data transformation and modeling workflows.
- Problem-Solving Skills: Excellent problem-solving skills, analytical thinking, and attention to detail.
- Communication Skills: Strong communication and interpersonal skills, with the ability to collaborate effectively in a team environment.
- Adaptability: Eagerness to learn and adapt to new technologies and tools in a fast-paced environment.
Estimated Salary: ₹1,200,000 - ₹2,400,000 per annum, based on industry standards and location.
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