Roche
Pune
Biotech & Pharmaceutical
DESCRIPTION
We are building the Next generation of Healthcare diagnostics analytics with a culture of data-driven insight and innovation. If you are ready to use your creativity and results-oriented critical thinking to meet complex challenges and develop new strategies for acquiring, analyzing, modelling and storing data, apply for our Data Architect opening.
We are looking for someone to guide data engineering and QA teams. Utilize the latest technology and information management methodologies to meet our requirements for effective logical data modelling, metadata management and database warehouse domains.
LOCATION
Pune, India
KEY RESPONSIBILITIES
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Develop architectural strategies for data modeling, design and implementation to meet stated requirements for metadata management, master data management. Data warehouses, ETL and ELT.
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Review existing data architectures to determine overall effectiveness and adherence with objectives, develop plans and strategies to improve.
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Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.
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Creation of functional design deliverables, data models, perform design walk-through, transition design and data models to teams, and support during testing and deployment.
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Analyzing business requirements, designing scalable/ robust data models, documenting conceptual, logical & physical data model design, helping developers in development/ creating DB structures and supporting developers throughout the project life cycle.
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Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
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Lead and Mentor Data Engineers: This role will be responsible for leading and developing a team of data engineers focused on the growth in the team’s skills and ability to execute as a team using DevOps and Data Ops principles. Also, collaborate with Data Engineering and Governance teams in building Data Lake, EDW by ingesting data from various sources to enable the advanced analytical capabilities.
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Investigate new technologies, data modeling methods and information management systems to determine which ones should be incorporated onto data architectures, and develop implementation timelines and milestones.
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Recognizes and resolves conflicts between models, ensuring that information and data models are consistent with the ecosystem model (e.g., entity names, relationships and definitions). Reviews information and data model designs with a focus on those areas influencing interoperability, analytics including compliance with the portfolio information model. Participates in the design of the information architecture: supports projects, reviews information elements including models, glossary, flows, data usage. Provides guidance to Business Analysts, Solution Architects, UX Experts, BI Analysts and Engineers, as well advises business how to increase enterprise information value. Works independently within broad guidelines and policies, with guidance in only the most complex situations.
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Contribute as an expert to multiple delivery teams, defining best practices, building reusable design & components, capability building, aligning industry trends and actively engaging with wider data communities.
REQUIRED EXPERIENCE, SKILLS & QUALIFICATIONS
To succeed in this role, you should have the following skills and experience
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Graduate or post graduate in Computer science/Electronics/Software engineering.
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6+ years of relevant experience in Data modeling for DW & analytics applications (OLAP) / Database related technologies.
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Expert data modeling skills (i.e. conceptual, logical and physical model design, experience with Enterprise Data Warehouses and Data Marts).
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Must have experience with at least one DB modelling tool like Erwin, MYSQL Workbench, DB Schema etc.
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Experience in designing Multi-tenant SaaS database & tenancy patterns.
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Expert level knowledge in two or more of the following subject areas specialisms.
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Data Engineering patterns and practices for efficient & optimized utilization from raw data
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Data Warehousing, semantic layer definitions and scaled data consumption patterns.
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Distributed compute and processing data in parallel.
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Robust enterprise grade data integration, ingestion, management & pipelines.
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Data streaming and associated “Lambda & Kappa” style data architectures.
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Solid understanding of cloud database technologies and services (eg..Snowflake, Redshift, Aurora, DynamoDB, etc)
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Experience in working with data governance, data quality, and data security teams. Specifically privacy and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification.
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Experienced in knowledge-driven data processing techniques like data curation, representation, standardization, normalization and any other type of processing that prepares the data for integration, persistence, analysis, exchange/share and so forth.
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Experience in handling very large DBs and large data volumes
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Strong experience with popular database programming languages including SQL, PL/SQL, etc. for relational databases like RedShift, Aurora and on NoSQL/Hadoop oriented databases like MongoDB, Cassandra, etc for non relational databases.
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Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include ETL/ELT, data replication/CDC, message-oriented data movement and upcoming data ingestion and integration technologies such as stream data integration and data virtualization.
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Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production.
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Experience working with popular data discovery, analytics, and BI software tools like MicroStrategy, Tableau, Qlik, Power BI and others for semantic-layer-based data discovery. Certification in one more of these tools would be a plus.
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Proven track record of building and delivering enterprise-class products.
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Crisp and effective executive communication skills, including significant experience presenting cross-functionally and across all levels.
DESIRED EXPERIENCE, SKILLS & QUALIFICATIONS
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Experience in Healthcare/Laboratory domain is a plus
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Experience in developing business intelligence/analytics applications or software for multi-tenant enterprise SaaS applications is desirable
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Experience working with popular data discovery, analytics and BI software tools like MicroStrategy, Tableau, Qlik, PowerBI and others for semantic-layer-based data discovery.
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Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms.
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Experience with columnar databases such as Vertica or experience in other Big-data technologies is a plus
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Strong experience with analytical methods including regression, forecasting, time series, cluster analysis, classification, etc. Experience with machine learning and AI would be a plus.
EDUCATION
Bachelor’s or Master’s in in Computer science/IT/Computer Applications/Software engineering/Electronics
Job Level:
Individual contributor
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