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Your key responsibilities
Ability to clearly explain data and analytics strengths and weaknesses to both technical and senior business stakeholders
Develop and maintain strong effective working relationships with key management personnel and internal client base including data engineers, BA’s and directly with the services/businesses
Responsible for developing batch ingestion and data transformation routines using ETL tools or other ingestion techniques
Responsible for developing real-time ingestion and data transformation routines using Kafka and similar technologies
Responsible for migrating data from legacy data platform to cloud data platform
Present data in graphs, charts, tables, etc. and designing and developing relational databases for collecting data.
Keep track of trends, patterns, and correlation in case of complex data sets.
Be involved in all aspects of the project life-cycle, including strategy, road-mapping, architecture and implementation to gain maximum exposure to set you up for a successful consulting career.
Configuration and coordination of data pipelines across projects
Data pipeline development, including Azure Data Factory, AWS Kinesis, Spark
Migration and transformation of large complex data sets from legacy systems like Teradata to cloud platform using Azure tools and other ETL tools like DataStage (ideally 5+ Years)
Data and Reporting Platform development on environments using technologies such as Microsoft Azure, SAP BW, Teradata, PowerBI or Cognos
Skills and attributes for success
Strong problem solver, someone comfortable to challenge the status quo
Knowledge and experience in end-to-end project delivery, either traditional SDLC or agile delivery methodologies (or hybrid approaches)
Leverage technology to continually learn, improve service delivery and maintain our leading-edge best practices
Strong presentation skills and proficiency in the use of PowerPoint, Word and Excel
Good understanding of financial services industry
To Qualify for the role, you must have
Bachelor or Master’s degree in computer science, Engineering, or other related fields.
Minimally 3 years of relevant experience. Preferably at least a year of experience in the consulting industry.
Understanding or even practical experience of handling and manipulating semi-structured and unstructured data.
Deep understanding of big data technology, concepts, tools, features, functions and benefits of different approaches available.
Experience with one of Java, C# or C++.
Hands-on experience with HiveQL.
Familiarity with data ingestion tools such as Kafka, Flume and Sqoop.
Knowledge of hadoop related workflow/scheduling tools such as Oozie.
A strong background in coding with possible experience with Python, SAS, SQL or R.
Project delivery toolset experience in one or more batch ETL tools (such as DataStage, Informatica, Microsoft SSIS, Azure Data Factory or Talend) OR open source data integration tools (such as Kafka or Nifi)
Ideally, you’ll also have
Experience in data and analytics approaches such as data mesh.
Previous experience working with data, data environments, databases, large data sets possibly in a consulting environment
Ability to deploy, manage, and administer Hadoop-based components.
Ability to design, build, install, configure and support Hadoop-based applications.
Experience with investigating and handling data quality issues.
Understanding of data modeling (ER models) techniques.
What we offer
Continuous learning:You’ll develop the mindset and skills to navigate whatever comes next.
Success as defined by you:We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
Transformative leadership:We’ll give you the insights, coaching and confidence to be the leader the world needs.
Diverse and inclusive culture:You’ll be embraced for who you are and empowered to use your voice to help others find theirs.
Apply now.
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
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