Cloud Data Lead – Public Cloud
1 month ago
The Cloud Data Lead is a senior person responsible to own end-to-end technical
responsibilities. Responsible for ensuring the best architecture and support are provided to
the customer on behalf of Getronics. This role will also be the technical & people POC for
the Public Cloud Delivery team customer engagements. This role will be also responsible
for supporting the transition phase of existing or new customers.
Responsibilities/Accountabilities
Prepare the KMAP of the team and create upskill / training plan
Review and update of Project specific documentation
Plan and guide team in Managing day-to-day activities
Assist in technology decision-making and proposing the best solution to the client for the capabilities/solutions we have during deal solution conversations
Contribute to developing platforms that make data across applications/application deployments available for AI/ML-driven feature prototyping, proofs-of-concept, and general availability
Assist in refining data pipelines for analysis, while refining, automating, and scaling as needed for the use case at hand
Work on various aspects of the AI/ML ecosystem – data modeling, data, and ML pipelines, data documentation, scaling, deployment, monitoring, and maintenance etc.
Work closely with Data scientists and MLOps Engineers to come up with scalable system and model architectures for enabling real-time ML/AI services
Develop, program, and maintain applications using the Apache Spark open-source framework
Work with different aspects of the Spark ecosystem, including Spark SQL, Data Frames, Datasets, and streaming
Familiar with big data processing tools and techniques Create Spark jobs for data transformation and aggregation
Produce unit tests for Spark transformations and helper methods
assist in designing data processing pipelines, creation and maintenance of optimal data pipeline architecture
Assemble large, complex data sets that meet functional / non-functional business requirements
Assist in building analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
Create data tools for analytics and data scientist team members that assist them in building and optimizing our offerings
Build processes supporting data transformation, data structures, metadata, dependency and workload management
Provide the team technical direction(s)/approach(es) to be undertaken and guide them in the resolution of queries/issues etc.
Attend/drive various architectural, design, and status calls with multiple stakeholders
Ensure end-to-end ownership of all tasks is aligned
Test implementation, troubleshooting & correct problems
Capable of working as an individual contributor and within a team too
Conduct technical training(s)/session(s), write whitepapers/ case studies / blogs etc
Required Technical Skills and Experience
More than 10+ years of experience which can include IT infrastructure, Cloud and Data areas
Minimum of 3 years experience managing a team containing a mix of Data skills
Strong analytic skills related to working with unstructured datasets
A successful history of manipulating, processing and extracting value from large, disconnected datasets
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data store
Agile/Scrum methodology experience is required
Expertise in designing and developing applications using Big Data and Cloud technologies.
Hands-on experience on Spark, and Hadoop echo system components
Hands-on experience of any of the Cloud (AWS/Azure)
Good knowledge of Shell script & Java/Python
Passionate about exploring new technologies.
Good Communication Skills
5+ years of experience understanding architecture-related distributed data systems, specifically within one of the following:
o Data Engineering technologies Spark, Hadoop, Kafka)
o Data Warehousing SQL, OLTP/OLAP/DSS)
o Data Science and Machine Learning technologies pandas, sci-kit-learn, HPO)
Knowledge of migration projects on Hadoop will be good to have
Knowledge of Agile Development will be good to have
Knowledge of one of the Workflow engines like Oozie, Autosys will be good to have
Expertise in preparing Proposal/SOW will be good to have
Certifications
In one or more of the following areas
o Data Engineering technologies Spark, Hadoop, Kafka)
o Data Warehousing SQL, OLTP/OLAP/DSS)
o Data Science and Machine Learning technologies pandas, sci-kit-learn,HPO)
Microsoft Azure or AWS Cloud or Data certifications
ITIL and or Agile methodologies
Educational Qualification
Bachelor/Masters’s Degree from a reputed institute
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