As a Senior Data Engineering, you will be a key leader in designing, implementing, and overseeing the data architecture. You will play a critical role in ensuring data solutions are scalable, secure, and aligned with the organisation's strategic goals. Your expertise will be crucial in guiding the team and collaborating with various stakeholders to drive innovation and deliver data-driven insights.
Responsibilities:
Team Leadership : Lead, mentor, and inspire a high-performing team of data engineers. Provide technical guidance and support to team members, ensuring their professional development.
Solution Design: Design and implement robust, scalable, and cost-effective data solutions on cloud platforms, encompassing data ingestion, storage, processing, and access layers.
Project Management: Define project scope, timelines, and deliverables and track project progress and ensure timely completion.
Stakeholder Management : Collaborate with business stakeholders to understand their data needs.Communicate project status, risks, and mitigation plans effectively to them.
Technology Evaluation & Selection: Stay updated of new services and technologies, evaluate their potential, and make recommendations for adoption.
Data Modeling & Design: Lead the design and implementation of dimensional data models (star schema, snowflake schema, etc.) to support efficient querying and reporting.
Data Governance: Establish and enforce data governance policies, standards, and procedures to ensure data quality, integrity, and security.
Performance Optimization: Proactively monitor and optimise data pipelines and queries for optimal performance and cost efficiency.
Documentation: Create and maintain comprehensive documentation for data architectures, data models, and processes.
Qualifications:
Proven experience as a Data Engineering manager, with a track record of successfully designing and implementing ETL/ELT data pipelines and systems.
Exceptional communication and presentation skills to interact with both technical and non-technical stakeholders.
Experience in SQL proficiency, specifically on Google Big Query is a plus.
Proficiency in programming languages such as Python/pySpark is plus.
Strong knowledge of data warehousing and data modelling concepts.
Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
Familiarity with Google Cloud Platform (GCP) services is an advantage.
Knowledge of data governance, data security and compliance practices.
Certifications in relevant technologies (e.g., AWS, Azure, Google Cloud,Snowflake) will be beneficial.
At LatentView Analytics, we value a diverse, inclusive workforce and we provide equal employment opportunities for all applicants and employees. All qualified applicants for employment will be considered without regard to an individual's race, color, sex, gender identity, gender expression, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws.