Data Engineering Lead, Singapore

About the job

Data Engineering Lead

At ofi, we are on a mission to leverage data to drive innovation and business transformation. We are looking for a Data Engineering Lead to spearhead our data engineering team and contribute to our mission of delivering data-driven solutions. As a Data Engineering Lead, you will be responsible for managing the data engineering team and overseeing the design and implementation of our data infrastructure. You will work closely with data scientists, analysts, and other stakeholders to ensure the seamless flow and integrity of data across the organization.

Key Responsibilities:

Data Infrastructure Management:

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  Design and Build Data Architecture: Construct robust data pipelines in the Snowflake environment (hosted in MS Azure) to support scalable data ingestion, transformation, and delivery.
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  Data Collection and Integration: Develop systems to collect data from various sources (including SAP ERP, Salesforce, other IT systems as well as OT systems) using real-time or batch ingestion technologies, ensuring it is accurately integrated into the Snowflake platform.
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  Data Transformation: Implement processes to normalize, aggregate, and transform data into a format suitable for analysis and reporting.
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  Performance Optimization: Optimize data retrieval and query performance within Snowflake, ensuring efficient operation of data pipelines.
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  Collaboration with Stakeholders: Work closely with business leaders to understand company objectives and align data engineering strategies accordingly.
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  Governance and Security: Partner with legal and cyber security teams to maintain high standards of data governance and security, ensuring compliance with relevant regulations.
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  Innovation and Improvement: Stay abreast of the latest technology innovations in data engineering and apply them to improve existing systems and processes.
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  Team Leadership: Lead and mentor a team of data engineers, fostering a culture of technical excellence and continuous learning.

Data Quality Assurance:

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  Collaborate with subject matter experts to establish data quality rules, standards, and thresholds for the data domains.
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  Develop and implement data quality metrics /standards, processes, and tools to monitor and improve the quality and accuracy of data across systems and platforms.
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  Implement data validation and cleansing routines to identify and rectify data errors, duplicates, outliers, and missing values, leveraging data quality tools such as Informatica.
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  Conduct data profiling and analysis to identify data quality issues, inconsistencies, and anomalies and work with relevant teams to address them.
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  Implement data lineage and metadata management solutions to track the origin, transformations, and usage of data across the organization.

Requirements

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  Bachelor’s or master’s degree in Computer Science, Data Analytics, Data Science, Information Technology, etc.
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  Proven 6+ years of experience in data engineering, with 2+ years as the Data Engineering Lead.
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  Knowledge of SAP ERP (S4HANA and ECC) including its integration with Snowflake.
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  Functional understanding of customer experience, manufacturing, supply chain, and financial concepts
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  Proficiency in data pipeline tools and technologies, particularly within the Snowflake ecosystem.
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  Extensive experience with SQL databases and multiple programming languages.
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  Experience in working with data quality tools such as Informatica.