Amgen seeks a Level 4 Data Engineer in Hyderabad to design and build data solutions, ETL pipelines, and data governance frameworks. The role involves working with large datasets, cloud platforms, and AI technologies to deliver actionable insights for business decisions.
Responsibilities
Design, develop, and maintain end-to-end data pipelines and ETL/ELT processes across systems
Build and optimize data solutions for collection, processing, and quality assurance
Implement data security, privacy measures, and governance frameworks to protect sensitive information
Collaborate with cross-functional teams including Data Architects, Business SMEs, and Data Scientists
Identify and resolve complex data challenges; explore tools to improve platform performance
Requirements
Master's or Bachelor's degree in Computer Science, IT, or related field with 5-9 years experience
Hands-on expertise with big data platforms including Databricks and Apache Spark
Proficiency in SQL and data visualization tools; strong data governance knowledge
Experience with ETL/ELT processes, data modeling, and data warehousing concepts
Familiarity with Python/R, AWS cloud platforms, and AI/LLM implementation
Strong problem-solving, communication, and collaborative teamwork abilities
Data protection and compliance regulations knowledge (preferred certification in Databricks or cloud environments)
... scalable data pipelines and third-party API integrations. - Work with business teams and analysts to interpret business rules and derive insights. - Implement data-quality processes, monitoring, and alerting to maintain accurate and available production data. - Analyze and troubleshoot data issues and assist with their resolution. ...
Baxter seeks a Data Engineer to develop and support ETL and data transformation jobs using PySpark and IBM DataStage in AWS. The role involves building new pipelines, enhancing existing systems, performing code reviews, and providing technical support for a global data warehouse. Responsibilities - Develop new ETL and data ...
... participate in design reviews, and help keep our schemas and contracts sane as the system grows What You'll Bring Must have - 1–3 years of professional software engineering experience, with meaningful exposure to data-intensive systems - Strong programming skills in Python, Java, or Scala, and the ability to write production-quality, ...
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... maintain scalable data engineering solutions.- Develop and manage ETL/ELT pipelines for data ingestion, transformation, and processing.- Work extensively with Databricks for data engineering and data processing requirements.- Develop and optimize data solutions using GCP BigQuery.- Develop data engineering solutions using ...
... experience with Hadoop / Big Data platforms.- Strong exposure to Big Data platform engineering and related technologies.- Experience working on/with complex data platforms and large-scale data environments.- The requirement is specifically for a Data Engineer / Big Data Engineer, not a generic application/development profile.- ...
... subordinate team members to meet established timelines. Requirements - 3–5 years of experience. - Knowledge of SQL and Python. - Experience or knowledge of data engineering, data modelling, ETL/ELT development, data pipelines, cloud data platforms, database management, data warehousing, and data lakes. - Knowledge of data analysis, ...
... and analytics. - Implement data quality checks, validation frameworks, monitoring, error handling, and pipeline performance improvements. - Collaborate with Data Analysts, Data Scientists, Product Teams, and Business Stakeholders to understand requirements and deliver scalable data solutions. - Follow data engineering ...
Amgen seeks a Level 4 Data Engineer to design, build, and maintain data solutions that drive business decisions. The role involves developing ETL pipelines, managing large datasets, implementing data governance, and collaborating across teams to deliver scalable data infrastructure. Responsibilities - Design, develop, and ...
... effective solutions - Ensure adherence to best practices related to data governance, quality, and security across all data pipelines - Automate and optimize data processing tasks to improve reliability and reduce manual intervention - Drive adoption of emerging big data technologies, cloud engineering, and automation practices ...