Senior Specialist, Data Engineering

Job Details

Title: Senior Specialist, Data Engineering

Key Accountabilities

Data integration:

- Develop and implement comprehensive data integrations in collaboration with Network & application engineers to support business requirements.

- Ensure data flow compliance with industry legislative and regulatory requirements.

- Design and implement data integration strategies for seamless data exchange across multiple domains.

- Build & Manage API gateway, ETL/ELT processes, Pub/Sub where required and ensure data consistency, integrity, and security.

Hybrid Environment Management:

- Manage data integration / publication / virtualization (where required) in a hybrid environment, integrating on-premises and cloud systems.

- Monitor and troubleshoot data integrations & data flow issues in both environments.

Collaboration and Stakeholder Engagement:

- Collaborate with network engineer/solutions engineer, architects, analysts, and business stakeholders to understand data requirements and deliver appropriate solutions.

- Provide technical guidance and support to team members and stakeholders.

Documentation and Compliance:

- Maintain detailed documentation of data pipelines; Cadance of data flow; protocol; details etc. DFDs and integration processes.

- Conduct regular audits and reviews to ensure data architecture accuracy and compliance.

Project Management:

- Provide regular updates to stakeholders on project progress and outcomes.

Innovation and Continuous Improvement:

- Stay updated with the latest trends and technologies in data integration.

- Identify opportunities for process improvement and optimization.

- Lead initiatives to implement new tools and technologies enhancing data integration & data flow capabilities.

- Provide input to the architectural strategy and road map for the Data and Information Domain.

- Provide content regarding Data and Information frameworks as well as design processes for implementation.

- Monitor technology capabilities, trends, and requirements, such as emerging standards for new technology opportunities.

- Provide subject matter expertise to ensure strategic direction in Data and Information Management.

- Keep up to date with the data elements available within the company.

- Provide advice on supplier and cost options, ensuring the validity of solutions in the RFI/RFP process.

- Participate in broader architectural governance activities and peer reviews for other solutions.

- Provide leadership in planning, development, and execution of Group solutions.

- Ensure governance standards in the context of Data and Analytics Management are adhered to.

Job Purpose

Responsible for ensuring that the data and information architecture is strategically managed, implemented, and enforced within the organization. The role will directly support the organization’s future strategy and business model, transforming data into meaningful information that drives effective decision-making capabilities.

Qualifications, Experience, Skills & Competencies

Education:

-Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field.

-TOGAF certified in Enterprise Architecture is an advantage.

- Certification in Azure cloud is an advantage.

Technical Skills:

Proficiency in more than one ETL/ELT tools (Talend, Informatica, Apache NiFi, Google BigQuery, Azure Data Factory).

Strong experience in CI/CD pipeline development and maintenance.

Expertise in data integration in some of these protocols (REST, SOAP, GraphQL, FTP, SFTP, FTPS, ODBC, JDBC, DB Link, IBM MQ, RabbitMQ, AMQP, JMS, Kafka, Apache Pulsar, Kinesis, gRPC, XML-RPC).

Skill & advanced knowledge in some of the virtualization technologies and platforms (ODBC/JDBC for Virtualization, Denodo).

Proficiency in scripting and programming languages (Python, Java, SQL).

Experience:

- Minimum 15 years of experience as a Data Engineer in a large-scale enterprise environment.

- 10-12 years in data engineering, with significant projects & transformation exposure & experience.

- Extensive experience with Azure and Google Cloud Platform (GCP).-

- Proven track record in designing and implementing data analysis strategies and data management processes.

- Experience with cloud platforms such as Azure, or GCP, including deploying cloud-based storage and analytics services.

Hands-on experience on Databricks, PowerBI,

Advanced knowledge of virtualization technologies and platforms (ODBC/JDBC for Virtualization, Denodo).

- Familiarity with industry-specific data techniques and regulations, with relevant experience in sectors like B2B & B2C , CX of high traffic data or e-commerce.