Sapwood Ventures Pvt. Ltd.
seeking an exceptional individual to lead and manage a team of data engineers and analytics engineers. Data Engineering team design, builds and maintain the data infrastructure and platform for all our projects and products. As the head of Data Engineering, you will be instrumental in defining and implementing our core infrastructure and help us realize our
data-driven mission of creating data driven solutions.
You will work closely with Data scientists, Engineers, Product team, Designers, and others in a cross-functional environment on multiple projects. You will also have the opportunity to lead a variety of projects involving data pipelines, data management, machine learning infrastructure, and API design and development,
in cloud-based application stack.
As a Head of Data Engineering, you will work on diverse data technologies such as Spark, Presto, Flink, Kafka, Camel and others to build insightful, scalable and robust data tools and frameworks to enable efficient data products. You will be responsible for ensuring data is flowing through right systems and delivering value via various data management tools.
Roles and Responsibilities
Design and build software components that implement key aspects of the full data lifecycle, including acquisition, transformation, management, export, and analytics
Design a secure, highly extensible and reliable platform to consume, integrate and analyze complex data using a variety of best-in-class open-source platforms and tools
Design the data infrastructure architecture for driving large-scale data science projects Create the software that enables our industry-leading machine learning insights to be delivered at enterprise scale
Build APIs and interfaces to deliver key analytic and data science insights
Identify opportunities for data-driven applications that could measurably improve the data scientists, data engineers, and businesss efficiency through automation and machine learning Partner with cross-functional teams and Data Subject Matter Experts to interpret, translate, and prescribe requirements
Drive a holistic information management strategy including capability roadmaps across advanced analytics, big data, and cloud-based platforms
Analyze latest Big Data Analytic technologies and their innovative applications for continuous improvement in data engineering and data processing
Collaborate with IT teams to develop Big Data reference architecture patterns for data ingestion, data processing, analytics, and data science solutions
8+ years of industry experience working with distributed data technologies (e.g. Hadoop, MapReduce, Spark, etc.) & cloud infrastructure for building efficient, large-scale data pipelines. A strong background in distributed data processing & software engineering and the ability to build high-quality, scalable data products.
Strong knowledge of data architectures, databases, data modeling, and the data infrastructure ecosystem.
Expertise in designing end-to-end data engineering solutions using a variety of data integration and processing patterns
Experience building stream-processing applications using Apache Flink, Spark-Streaming, Apache Storm, Kafka Streams, or others
Experience with NoSQL, relational databases (such as MySQL, Postgres) and analytics databases (such as Druid, Apache Pinot).
Experience with cloud computing platforms such as Amazon AWS, Google Cloud, Microsoft Azure Experience with Containers and Kubernetes, CI/CD tools like Jenkins
Thorough understanding of data lake/warehouse architectures (BigQuery, Snowflake, RedShift) Strong Software Engineering experience and proficiency in at least one high-level programming language (Java, Scala, Python or equivalent).
Graduate/Postgraduate in computer science, engineering, mathematics, statistics or a related field OR equivalent practical experience in data engineering
Expert knowledge of Big Data and data warehouse concepts in Retail/CPG industries
Interested candidates can forward your updated resumes to
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