Conduct discovery sessions, analyze requirements, and design solutions.
Design and implement processes for data acquisition, storage, transformation, and retrieval from various sources, ensuring data quality and integrity but also seamless integration of large-scale datasets allowing our clients to fully leverage the value of their investment into their Data Lake and alike.
Technology Lead/SME:
Lead project planning, execution, and delivery activities, ensuring alignment with business objectives, timelines, and quality standards.
Identify, manage, and resolve any risks, issues, and blockers.
As the SME on AWS Data technologies, serve as technical lead on customer engagements and internal initiatives, providing technical guidance and leadership to delivery teams.
Providing leadership on engagements, including balancing team and individual responsibilities; building teams and consensus; getting things done through others not directly under their supervision; and working ethically and with integrity.
Stay embedded with the Data delivery teams to understand functional and non-functional requirements, remove roadblocks, and analyze feasibility.
Foster a culture of innovation and continuous learning within the team.
Identify areas for improvement and increase the productivity of the Delivery team.
Best Practices:
Ensure the development of robust, scalable Data solutions and platforms by providing technical oversight and aligning with AWS best practices.
Establish and maintain best practices for engagement delivery and leverage frameworks consistent with and supportive of the AWS Data technologies and architectural approach.
Promote and ensure delivery teams’ adherence to Agile methodology and Scrum framework.
Communication & reporting:
Establish and ensure regular and effective communication with all required stakeholders, translating complex Data concepts into understandable insights and updates.
Implement mechanisms to monitor, manage, and provide progress on all engagement activities and team performance and establish regular reporting to leadership.
Requirements & Skills:
Data Expertise:
Expert knowledge of Data concepts and methodologies, including databases, data lakes, data warehousing, data lakes, data governance, and data security.
Expert knowledge in the data best practices captured by AWS Well-Architected Framework – Data Lens.
Leadership:
Demonstrable experience in consulting, architecting/solution, and leading multi-workstream Data engagements in an enterprise setting.
AWS Data:
Expert knowledge in AWS Data integration, ingestion, storage, processing, and visualization technologies across structured and unstructured data sources, along with various enterprise applications.
Expert knowledge in modern data architecture and platforms, such as cloud, data mesh, data lakehouse, delta lake, and data warehousing.
Experience in migrating data platform applications from on-prem to AWS.
Code:
Expert knowledge of SQL languages with a strong programming skill in Python or Spark/Scala.
Advanced knowledge in code repositories, code development processes, and code reviews.
AWS Infrastructure & AI:
Expert knowledge in AWS infrastructure technologies, such as CDK, CloudFormation, AWS Step Functions, EC2, and IAM).
Demonstrable knowledge in Amazon Bedrock and SageMaker JumpStart.
Problem-Solving: Strong analytical and problem-solving skills, with the ability to think critically and creatively.
Communication: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Autonomy: Ability to work independently and in a team.
Learning: An interest in continuously upskilling for a digital-first world and embracing technology trends, an openness to learning new tools, and adapting how you work.
Education: Bachelor’s degree in a quantitative field (Computer Science, Machine Learning, Operational Research, Statistics). A master’s or PhD degree in a relevant field is a bonus.
