Senior Specialist, Observability Data Engineer

Job description

Job Description Senior Specialist, Observability Data Engineer The Opportunity Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats. Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company’s IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy. A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers. Role Overview A Data Engineer is responsible for designing, building, and maintaining robust data pipelines/reports and infrastructure that facilitates the collection, storage, and processing of large datasets. They ensure data/insight is accessible, reliable, and optimized for analysis by collaborating with data scientists and analysts. Key tasks include data ingestion, integration, ETL (Extract, Transform, Load) processes, report design and managing databases and cloud-based systems. Data engineers play a crucial role in enabling data-driven decision-making and ensuring data quality across organizations. Additionally, as an Observability Data Engineer in the Company, you will help shaping the foundational capabilities that make enterprise data reliable, measurable, and scalable. Embedded in Core Data & Engineering and working with a global team, you will design and operate observability and optimization capabilities used by product and delivery teams across platforms. Your work enables faster detection of issues, better performance and cost visibility, and continuous improvement across data pipelines and products. What will you do in this role Design, implement, and maintain complex data engineering solutions to acquire and prepare data. Create and maintain data pipelines to connect data within and between data stores, applications and organisations. Support and monitor the implementation of information, record management policies, standard practice, effective control for internal delegation, audit and control relating to information and records management. Monitor performance statistics, create reports, Identify and investigate complex problems, issues and recommend corrective actions. Perform routine configuration, installation, and reconfiguration of database and related products. Identify issues related to software development activities and propose practical solutions to resolve issues. Apply variety of visualisation techniques, design the content, appearance of data visuals. Operationalise and automate activities for efficient and timely production of data visuals. Establish, modify, maintain and communicate the details of the data structures and associated components to others using the data structures, standard data modelling and design techniques. Support business intelligence needs of specific management or governance processes or operational areas. Investigate the need for business intelligence reporting and analysis where there is some complexity and ambiguity. Prepare design options for the working environment of methods, procedures, techniques, tools, and people. Select systems and software life cycle working practices for software components and micro-services. Create and document detailed designs for simple software applications and components. And contribute to the design of components of larger software systems. Establish, modify and maintain data structures and associated components. Create and deliver standard reports in accordance with stakeholder needs and conforming to agreed standards. Work within a matrix organizational structure, reporting to both the functional manager and the project manager. Participate in project planning, execution, and delivery, ensuring alignment with both functional and project goals. Design, implement, and operate data observability capabilities, including metrics, logs, alerts, and signals to ensure reliability, availability, and security of data workloads. Provide L3 production support for data platforms and products, acting as an engineering subject matter expert for troubleshooting, incident resolution, and adoption support. Develop and maintain engineering runbooks, operational guides, best practices, and reference architectures for platform operations and support. Design and automate scalable onboarding patterns for new data sources and connection types into shared data platforms. What should you have Primary skills : Data Ingestion, Python, SQL, AWS Secondary skills : Databricks,kafka(good to have) Bachelors’ degree in Information Technology, Computer Science or any Technology stream. 7+ years of developing data pipelines & data infrastructure, ideally within a drug development or life sciences context. Demonstrated expertise in delivering large-scale information management technology solutions encompassing data integration and self-service analytics enablement. Experienced in software/data engineering practices (including versioning, release management, deployment of datasets, agile & related software tools). Strong working experience of at least one data ingestion and one data curation tool (can be open source, cloud-native or commercial/enterprise). Strong working knowledge of at least one large-scale data processing technology (e.g., High-performance computing, distributed computing), databases, and underlying technology (cloud or on-prem environments, containerization, distributed storage & databases). Practical experience working with the Databricks platform and a good understanding of its core principles (including Delta Lake, Spark workloads, notebook workflows, cluster management). Cloud-native, ideally AWS certified. Very good skills in Python and SQL. Good interpersonal and communication skills (verbal and written). Proven record of delivering high-quality results. Product and customer-centric approach. Innovative thinking, experimental mindset. Experience with data observability tooling or frameworks is an advantage. Handson Apache Airflow experience (deployment, DAG troubleshooting, scaling) is an advantage. Our technology teams operate as business partners, proposing ideas and innovative solutions that enable new organizational capabilities. We collaborate internationally to deliver services and solutions that help everyone be more productive and enable innovation. Who we are We are known as Merck & Co., Inc., Rahway, New Jersey, USA in the United States and Canada and MSD everywhere else. For more than a century, we have been inventing for lives, bringing forward medicines and vaccines for many of the world's most challenging diseases. Today, our company continues to be at the forefront of research to deliver innovative health solutions and advance the prevention and treatment of diseases that threaten people and anim