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15 Weeks ago

BI & Data Warehouse Data Engineer

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Information Technology
Other
Astellas

Overview

DigitalX our new information technology function is spearheading this value driven transformation across Astellas. We are looking for people who excel in embracing change, manage technical challenges and have exceptional communication skills.

This position is based in Bengaluru and will require some on-site work.

Purpose and Scope:

As a Junior Data Engineer, you will play a crucial role in assisting in the design, build, and maintenance of our data infrastructure focusing on BI and DWH capabilities. Working with the Senior Data Engineer, your foundational expertise in BI, Databricks, PySpark, SQL, Talend and other related technologies, will be instrumental in driving data-driven decision-making across the organization. You will play a pivotal role in building maintaining and enhancing our systems across the organization. This is a fantastic global opportunity to use your proven agile delivery skills across a diverse range of initiatives, utilize your development skills, and contribute to the continuous improvement/delivery of critical IT solutions.

Essential Job Responsibilities:

    Collaborate with FoundationX Engineers to design and maintain scalable data systems.

    Assist in building robust infrastructure using technologies like PowerBI, Qlik or alternative, Databricks, PySpark, and SQL.

    Contribute to ensuring system reliability by incorporating accurate business-driving data.

    Gain experience in BI engineering through hands-on projects.

    Data Modelling and Integration:

    Collaborate with cross-functional teams to analyse requirements and create technical designs, data models, and migration strategies.

    Design, build, and maintain physical databases, dimensional data models, and ETL processes specific to pharmaceutical data.

    Cloud Expertise:

    Evaluate and influence the selection of cloud-based technologies such as Azure, AWS, or Google Cloud.

    Implement data warehousing solutions in a cloud environment, ensuring scalability and security.

    BI Expertise:

    Leverage and create PowerBI, Qlik or equivalent technology for data visualization, dashboards, and self-service analytics.

    Data Pipeline Development:

    Design, build, and optimize data pipelines using Databricks and PySpark. Ensure data quality, reliability, and scalability.

    Application Transition: Support the migration of internal applications to Databricks (or equivalent) based solutions. Collaborate with application teams to ensure a seamless transition.

    Mentorship and Leadership: Lead and mentor junior data engineers. Share best practices, provide technical guidance, and foster a culture of continuous learning.

    Data Strategy Contribution: Contribute to the organization’s data strategy by identifying opportunities for data-driven insights and improvements.

    Participate in smaller focused mission teams to deliver value driven solutions aligned to our global and bold move priority initiatives and beyond.

    Design, develop and implement robust and scalable data analytics using modern technologies.

    Collaborate with cross functional teams and practises across the organisation including Commercial, Manufacturing, Medical, DataX, GrowthX and support other X (transformation) Hubs and Practices as appropriate, to understand user needs and translate them into technical solutions.

    Provide Technical Support to internal users troubleshooting complex issues and ensuring system uptime as soon as possible.

    Champion continuous improvement initiatives identifying opportunities to optimise performance security and maintainability of existing data and platform architecture and other technology investments.

    Participate in the continuous delivery pipeline. Adhering to DevOps best practises for version control automation and deployment. Ensuring effective management of the FoundationX backlog.

    Leverage your knowledge of data engineering principles to integrate with existing data pipelines and explore new possibilities for data utilization.

    Stay-up to date on the latest trends and technologies in data engineering and cloud platforms.

Qualifications:

Required

    Bachelor's degree in computer science, Information Technology, or related field (master’s preferred) or equivalent experience

    1-3+ years of experience in data engineering with a strong understanding of BI technologies, PySpark and SQL, building data pipelines and optimization.

    1-3 +years + experience in data engineering and integration tools (e.g., Databricks, Change Data Capture)

    1-3+ years + experience of utilizing cloud platforms (AWS, Azure, GCP). A deeper understanding/certification of AWS and Azure is considered a plus.

    Experience with relational and non-relational databases.

    Any relevant cloud-based integration certification at foundational level or above. (Any QLIK or BI certification, AWS certified DevOps engineer, AWS Certified Developer, Any Microsoft Certified Azure qualification, Proficient in RESTful APIs, AWS, CDMP, MDM, DBA, SQL, SAP, TOGAF, API, CISSP, VCP or any relevant certification)

    Experience in MuleSoft (Anypoint platform, its components, Designing and managing API-led connectivity solutions).

    Experience in AWS (environment, services and tools), developing code in at least one high level programming language.

    Experience with continuous integration and continuous delivery (CI/CD) methodologies and tools

    Experience with Azure services related to computing, networking, storage, and security

    Understanding of cloud integration patterns and Azure integration services such as Logic Apps, Service Bus, and API Management

Preferred

    Subject Matter Expertise: possess a strong understanding of data architecture/ engineering/operations/ reporting within Life Sciences/ Pharma industry across Commercial, Manufacturing and Medical domains.

    Other complex and highly regulated industry experience will be considered across diverse areas like Commercial, Manufacturing and Medical.

    Data Analysis and Automation Skills: Proficient in identifying, standardizing, and automating critical reporting metrics and modelling tools

    Analytical Thinking: Demonstrated ability to lead ad hoc analyses, identify performance gaps, and foster a culture of continuous improvement.

    Technical Proficiency: Strong coding skills in SQL, R, and/or Python, coupled with expertise in machine learning techniques, statistical analysis, and data visualization.

    Agile Champion: Adherence to DevOps principles and a proven track record with CI/CD pipelines for continuous delivery.

Working Environment

At Astellas we recognize the importance of work/life balance, and we are proud to offer a hybrid working solution allowing time to connect with colleagues at the office with the flexibility to also work from home. We believe this will optimize the most productive work environment for all employees to succeed and deliver. Hybrid work from certain locations may be permitted in accordance with Astellas’ Responsible Flexibility Guidelines.

#LI-CH1

Category FoundationX

Astellas is committed to equality of opportunity in all aspects of employment.

EOE including Disability/Protected Veterans

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