Job Description

About Leading-Biotechnology-CompanyANSR, a market leader in enabling organizations to build, manage and scale global teams, is partnering with a renowned biotechnology company who is redefining the future of human health by providing solutions to some of the most complex problems in the healthcare industry. They are committed to making precision medicine accessible and carries out their business operations in an environmentally sustainable way.Now is your opportunity to join their innovative team in Bengaluru, India. For over 20 years now, companies cutting across size, industry and markets have relied on ANSRs expertise to successfully build global business and technology teams. We can help you land a rewarding career in this dynamic industry.If you are eager to contribute to a company with strong values, a supportive environment and where you get opportunities to work on challenging projects that uses cutting-edge technology to improve millions of lives, this is your chance to join a truly remarkable team. Apply today!We are seeking a highly experienced Staff Data Engineer with 10+ years of experience to join our talented team in Bangalore. This position will lead our data engineering efforts in Bangalore. In this strategic role, you will be responsible for designing, implementing, and optimizing complex data solutions using Python, Spark, SQL, Snowflake, dbt, machine learning, and other relevant technologies. Additionally, you will bring deep domain expertise in operations organizations, with a focus on supply chain, product life cycle management, and manufacturing functions. Experience with SAP Hana and Teamcenter applications is a plus. If you're a seasoned data engineer with a proven track record of delivering impactful data solutions in operations contexts, we want to hear from you.Position Responsibilities:

• Lead the design, development, and optimization of complex data solutions using Python, Spark, SQL, Snowflake, dbt, machine learning, and other relevant technologies.
• Apply deep domain expertise in operations organizations, particularly in functions like supply chain, product life cycle management, and manufacturing, to understand data requirements and deliver tailored solutions.
• Utilize big data processing frameworks such as Apache Spark to process and analyze large volumes of operational data efficiently.
• Implement advanced data modeling, machine learning algorithms, and predictive analytics to derive actionable insights and drive operational decision-making.
• Leverage cloud-based data platforms such as Snowflake to store, manage, and analyze structured and semi-structured operational data at scale.
• Utilize dbt (Data Build Tool) for data modeling, transformation, and documentation to ensure data consistency, quality, and integrity.
• Monitor and optimize complex data pipelines, ETL processes, and machine learning models for performance, scalability, and reliability in operations contexts.
• Conduct data profiling, cleansing, and validation to ensure data quality and integrity across different operational data sets.
• Collaborate closely with cross-functional teams, including operations stakeholders, data scientists, business analysts, and IT teams, to understand operational challenges and deliver actionable insights.
• Stay updated on emerging technologies, best practices, and industry trends in data engineering, machine learning, and operations management, contributing to continuous improvement and innovation within the organization.
• All listed requirements are deemed as essential functions to this position; however, business conditions may require reasonable accommodations for additional tasks and responsibilities.

• Bachelor's degree in Computer Science, Engineering, Operations Management, or related field. Advanced degree (e.g., Master's or PhD) preferred.
• 10+ years of experience in data engineering, with proficiency in Python, Spark, SQL, Snowflake, dbt, machine learning, and other relevant technologies.
• Strong domain expertise in operations organizations, particularly in functions like supply chain, product life cycle management, and manufacturing.
• Strong domain expertise in life sciences manufacturing equipment, with a deep understanding of industry-specific challenges, processes, and technologies.
• Experience with big data processing frameworks such as Apache Spark and cloud-based data platforms such as Snowflake.
• Hands-on experience with data modeling, ETL development, machine learning, and predictive analytics in operations contexts.
• Familiarity with dbt (Data Build Tool) for managing data transformation and modeling workflows.
• Excellent problem-solving skills, analytical thinking, and attention to detail.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and operations stakeholders.
• Experience with SAP, SAP HANA and Teamcenter applications is a plus.
• Eagerness to learn and adapt to new technologies and tools in a fast-paced environment.

Leading-Biotechnology-Company