Cloud Data Engineer ROCGJP00027944 A leading biotechnology company is seeking a highly skilled and motivated Cloud Data Engineer to join our growing data team. The ideal candidate will have a strong background in developing data pipelines, implementing data models, and executing best practices for developing data products. This role requires expertise in AWS, GitLab CI/CD, dbt, Snowflake, SQL, Python, Git, and DevOps, as well as hands-on experience with orchestrators such as Airflow and AutoMateNow, and data governance technologies like Monte Carlo and Collibra. Cloud Data Engineer Pay and Benefits: Hourly pay: $70-$80/hr (pay varies based on candidate's experience) Worksite: Leading biotechnology company (South San Francisco, CA 94080) W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL 40 hours/week, 7 Month Assignment Cloud Data Engineer Responsibilities: Develop Data Pipelines: Design, develop, and maintain robust, scalable, and efficient ETL/ELT pipelines to support diverse data sources and large-scale data processing. Data Modeling: Create and maintain data models and data architecture to ensure data integrity and optimum performance. Best Practices Implementation: Apply industry best practices in data warehousing, data governance, and data lifecycle management. Collaboration: Work closely with data scientists, analysts, and other stakeholders to gather requirements and deliver high-quality data products. Automation and CI/CD: Implement CI/CD pipelines using GitLab for automated testing, deployment, and integration of data workflows. Database Management: Manage and optimize Snowflake databases for performance, scalability, and cost-effectiveness. Coding and Scripting: Write efficient SQL queries and Python scripts to extract, load, and transform data. Version Control: Utilize Git for version control, ensuring traceable and manageable code changes. Orchestration: Utilize orchestration tools like Airflow and AutoMateNow to manage and automate data workflows. Data Governance: Implement and manage data governance and data observability solutions using technologies like Monte Carlo and Collibra. Monitoring and Optimization: Monitor data pipeline performance and troubleshoot issues to ensure reliability and efficiency. Documentation: Maintain comprehensive documentation for data pipelines, models, and processes. Cloud Data Engineer Qualifications: 5+ years of experience in data engineering or a similar role. Bachelors degree in Computer Science, Information Technology, Data Science, or a related field. AWS Certified Data Analytics Specialty or AWS Certified Solutions Architect. Proven experience with AWS cloud services related to data processing, such as S3, Redshift, Lambda, Glue, and Data Pipeline. Proficiency in designing and implementing CI/CD pipelines with GitLab. Experience with dbt (data build tool) for transforming data within the warehouse. Experience with orchestrators like Airflow and AutoMateNow. Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis). Experience in a regulated industry Experience in a manufacturing environment Strong knowledge of Snowflake with hands-on experience in data warehousing solutions. Expertise in SQL for data querying, manipulation, and optimization. Proficiency in Python for scripting and automation tasks. Familiarity with DevOps practices and tools. Knowledge of data governance and observability tools such as Monte Carlo and Collibra. Strong working knowledge of Git for version control. Strong problem-solving and analytical skills. Excellent communication skills, both written and verbal. Ability to work collaboratively in a fast-paced, dynamic environment. High attention to detail and commitment to producing high-quality work.

Job Title: (Technical Lead) AWS Data EngineerLocation: South SFO, CA (Hybrid role – 3 days/week onsite) Job Description:The role involves leading the design and management of data solutions in a cloud environment with a focus on AWS services. Responsibilities:· Lead the design, implementation, and optimization of scalable data pipelines and architectures utilizing AWS Glue, Elastic MapReduce (EMR), Lambda, Redshift, Athena, DynamoDB, OpenSearch, and S3.· Use Spark on AWS for data transformation and processing across large datasets.· Develop and maintain efficient data workflows with SQS for task queueing and orchestration.· Integrate, transform, and manage data using Mulesoft and Talend for seamless data integration.· Ensure high-performance data storage, retrieval, and analytics across Redshift, DynamoDB, and Athena.· Oversee data consistency, integrity, and compliance through IQVIA MDM solutions.· Apply best practices in data governance, security, and scalability within a collaborative and cross-functional team environment. Qualifications:· Proven expertise in AWS data engineering, specifically with Glue, EMR, Lambda, Redshift, Athena, DynamoDB, OpenSearch, and S3.· Strong experience with data integration (Mulesoft, Talend)· Working knowledge of master data management (proficiency in IQVIA MDM is a plus).· Demonstrated ability to lead technical projects and mentor data engineering teams.· Exceptional analytical and communication skills. If you are interested to pursue the opportunity, please send your updated resume to saikat.g@agiledatapro.com along with your rate / salary information

The Onyx Research Data Tech organization is GSK's Research data ecosystem which has the capability to bring together, analyze, and power the exploration of data at scale. We partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. The goal is to ensure scientists have the right data and insights when they need it to give them a better starting point for and accelerate medical discovery. Ultimately, this helps us get ahead of disease in more predictive and powerful ways.
Onyx is a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:
Building a next-generation, metadata- and automation-driven data experience for GSK's scientists, engineers, and decision-makers, increasing productivity and reducing time spent on "data mechanics"
Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent
Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time
Data Engineering is responsible for the design, delivery, support, and maintenance of industrialized automated end to end data services and pipelines. They apply standardized data models and mapping to ensure data is accessible for end users in end-to-end user tools through use of APIs. They define and embed best practices and ensure compliance with Quality Management practices and alignment to automated data governance. They also acquire and process internal and external, structure and unstructured data in line with Product requirements.
The Associate Data Engineer is a technical contributor who can take a well-defined specification for a function, pipeline, service, or other sort of component, and a technical approach to building it, and deliver it at a high level with guidance. They are aware of, and adhere to, best practice for software development in general (and data engineering in particular), including code quality, documentation, DevOps practices, and testing. They ensure robustness of our services and serve as an escalation point in the operation of existing services, pipelines, and workflows.
An Associate Data Engineer should have awareness of the most common tools (languages, libraries, etc) in the data space, such as Spark, Kafka, Storm, etc. They should be constantly seeking feedback and guidance to further develop their technical skills and expertise, and should take feedback well from all sources in the name of development.
Key responsibilities   Builds modular code / libraries / services / etc using modern data engineering tools (Python/Spark, Kafka, Storm, ...) and orchestration tools (e.g. Google Workflow, Airflow Composer)
Produces well-engineered software with guidance, including appropriate automated test suites and technical documentation
Ensure consistent application of platform abstractions to ensure quality and consistency with respect to logging and lineage
Adhere to QMS framework and CI/CD best practices
Provide L3 support to existing tools / services / pipelines
Contribute to knowledge management activities and follow best practices
Why you? Basic Qualifications:  We are looking for professionals with these required skills to achieve our goals:
Bachelor's degree in Data Engineering, Computer Science, Software Engineering or related field.
Software engineering experience
Experience with writing data processing pipelines
Experience with choosing appropriate data structures for scale and access patterns
Preferred Qualifications:   Exposure to automated testing techniques
Exposure to database concepts and SQL and grasp of relational and analytical database management theory and practice
Knowledge and use of at least one common programming language (e.g., Python, Scala, Java), including toolchains for documentation and testing
Exposure to modern software development tools / ways of working (e.g. git/GitHub, DevOps tools, ...)
Exposure to common tools for data engineering (e.g. Spark, Kafka, Storm, ...)
Nice to have experience in Big Data and NoSQL
Nice to have basic experience in cloud environments (AWS, Azure, GCP...)
#GSKOnyx, #LI-GSK and #GSKTech1   #earlycareers
The annual base salary for new hires in this position ranges from $82,025 to $110,975 taking into account a number of factors including work location within the US market, the candidate's skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.  Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a special purpose - to unite science, technology and talent to get ahead of disease together - so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns - as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).
Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it's also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves - feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.
If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).
GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.
Important notice to Employment businesses/ Agencies
GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK's compliance to all federal and state US Transparency requirements. For more information, please visit GSK's Transparency Reporting For the Record site.

Data Engineer Jobs in South San Francisco, CA

Cloud Data Engineer
December 7, 2024

Technical Lead Aws Data Engineer
November 28, 2024

Technical Lead Aws Data Engineer
November 24, 2024

Associate Data Engineer
November 24, 2024

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Data Engineer Jobs in South San Francisco, CA

Cloud Data EngineerDecember 7, 2024

Technical Lead Aws Data EngineerNovember 28, 2024

Technical Lead Aws Data EngineerNovember 24, 2024