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EY EY-GDS Consulting-AI DATA-AWS Databricks-python-Manager 
India, Karnataka, Bengaluru 
432294458

10.09.2024

The Senior Data Engineer will:

  • Clean, aggregate, and organize data from disparate sources and transfer it to data warehouses.
  • Support development testing and maintenance of data pipelines and platforms, to enable data quality to be utilized within business dashboards and tools.
  • Create, maintain, and support the data platform and infrastructure that enables the analytics front-end; this includes the testing, maintenance, construction, and development of architectures such as high-volume, large-scale data processing and databases with proper verification and validation processes.


Data Engineering

  • Design, develop, optimize, and maintain data architecture and pipelines that adheres to ETL principles and business goals.
  • Develop and maintain scalable data pipelines, build out new integrations using AWS native technologies to support continuing increases in data source, volume, and complexity.
  • Define data requirements, gather and mine large scale of structured and unstructured data, and validate data by running various data tools in the Big Data Environment.
  • Support standardization, customization and ad hoc data analysis and develop the mechanisms to ingest, analyze, validate, normalize, and clean data.
  • Write unit/integration/performance test scripts and perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
  • Implement processes and systems to drive data reconciliation and monitor data quality, ensuring production data is always accurate and available for key stakeholders, downstream systems, and business processes.
  • Lead the evaluation, implementation and deployment of emerging tools and processes for analytic data engineering to improve productivity.
  • Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.
  • Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
  • Solve complex data problems to deliver insights that help achieve business objectives.
  • Implement statistical data quality procedures on new data sources by applying rigorous iterative data analytics.


Relationship Building and Collaboration

  • Partner with Business Analytics and Solution Architects to develop technical architectures for strategic enterprise projects and initiatives.
  • Coordinate with Data Scientists to understand data requirements, and design solutions that enable advanced analytics, machine learning, and predictive modelling.
  • Support Data Scientists in data sourcing and preparation to visualize data and synthesize insights of commercial value.
  • Collaborate with AI/ML engineers to create data products for analytics and data scientist team members to improve productivity.
  • Advise, consult, mentor and coach other data and analytic professionals on data standards and practices, promoting the values of learning and growth.
  • Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.


Technical/Functional Expertise

  • Advanced experience and understanding of data/Big Data, data integration, data modelling, AWS, and cloud technologies.
  • Strong business acumen with knowledge of the Pharmaceutical, Healthcare, or Life Sciences sector is preferred, but not required.
  • Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.
  • Ability to build and optimize queries (SQL), data sets, 'Big Data' pipelines, and architectures for structured and unstructured data.
  • Experience with or knowledge of Agile Software Development methodologies.


Leadership

  • Strategic mindset of thinking above the minor, tactical details and focusing on the long-term, strategic goals of the organization.
  • Advocate of a culture of collaboration and psychological safety.


Decision-making and Autonomy

  • Shift from manual decision-making to data-driven, strategic decision-making.
  • Proven track record of applying critical thinking to resolve issues and overcome obstacles.


Interaction

  • Proven track record of collaboration and developing strong working relationships with key stakeholders by building trust and being a true business partner.
  • Demonstrated success in collaborating with different IT functions, contractors, and constituents to deliver data solutions that meet standards and security measures.


Innovation

  • Passion for re-imagining new solutions, processes, and end-user experience by leveraging digital and disruptive technologies and developing advanced data and analytics solutions.
  • Advocate of a culture of growth mindset, agility, and continuous improvement.


Complexity

  • Demonstrates high multicultural sensitivity to lead teams effectively.
  • Ability to coordinate and problem-solve amongst larger teams.


Essential skillsets

  • Bachelor’s degree in Engineering, Computer Science, Data Science, or related field
  • 5+ years of experience in software development, data science, data engineering, ETL, and analytics reporting development
  • Experience designing, building, implementing, and maintaining data and system integrations using dimensional data modelling and development and optimization of ETL pipelines
  • Proven track record of designing and implementing complex data solutions
  • Demonstrated understanding and experience using:
    • Data Engineering Programming Languages (i.e., Python)
    • Distributed Data Technologies (e.g., Pyspark)
    • Cloud platform deployment and tools (e.g., Kubernetes)
    • Relational SQL databases
    • DevOps and continuous integration
    • AWS cloud services and technologies (i.e., Lambda, S3, DMS, Step Functions, Event Bridge, Cloud Watch, RDS)
    • Databricks/ETL
    • IICS/DMS
    • GitHub
    • Event Bridge, Tidal
  • Strong organizational skills with the ability to manage multiple projects simultaneously and operate as a leading member across globally distributed teams to deliver high-quality services and solutions
  • Understanding of database architecture and administration
  • Processes high proficiency in code programming languages (e.g., SQL, Python, Pyspark, AWS services) to design, maintain, and optimize data architecture/pipelines that fit business goals
  • Extracts, transforms, and loads data from multiple external/internal sources using Databricks Lakehouse/Data Lake concepts into a single, consistent source to serve business users and data visualization needs
  • Utilizes the principles of continuous integration and delivery to automate the deployment of code changes to elevate environments, fostering enhanced code quality, test coverage, and automation of resilient test cases
  • Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners
  • Strong problem solving and troubleshooting skills
  • Ability to work in a fast-paced environment and adapt to changing business priorities


Desired skillsets

  • Degree in Engineering, Computer Science, Data Science, or related field
  • Experience in a global working environment


Travel requirements

  • Access to transportation to attend meetings
  • Ability to fly to meetings regionally and globally



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