Lead Data Engineer (Ukraine) #14667
Capgemini Engineering
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Purpose Of The Job
We are looking for a TechLead Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is a strategic thinker and hands-on technical leader, passionate about data architecture, performance optimization, and cloud-based data engineering. They should be self-directed, proactive, and comfortable driving data strategy, ensuring our infrastructure meets evolving business needs. You will work closely with software developers, database architects, data analysts, and data scientists to ensure a consistent, scalable, and high-performance data ecosystem across multiple teams, systems, and products.
Main Tasks And Responsibilities
Design and drive the development of scalable, high-performance data pipeline architectures, ensuring optimal data processing, transformation, and storage solutions
Assemble large, complete data sets that meet functional / non-functional business requirements
Lead the design and optimization of data infrastructure, leveraging modern data technologies to ensure scalability, reliability, and efficiency
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, performance, etc.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, revenue management, operational efficiencies, and other key business performance metrics
Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and their data infrastructure needs support
Keep our data separated and secure across national boundaries through multiple data centers and AWS regions
Create data tools for analytics and data scientist team members that assist them in building and optimizing our offerings
Work with data and analytics experts to strive for greater functionality in our data systems
Act as a technical advisor to engineering, product, and executive teams, translating business requirements into scalable data solutions
Education, Skills And Experience
MUST HAVE:
7+ years of experience in data engineering
1+ year in a lead or architect capacity designing and implementing scalable data solutions
Extensive experience working with relational databases and data warehouses, including BigQuery, PostgreSQL, Microsoft SQL Server, Oracle, etc.
Proficient in cloud technologies such as AWS/GCP/Azure, with flexibility to work with any cloud platform
Expertise in real-time and batch data processing using Spark/Kafka Streaming
Experience with programming and scripting languages: Python/Scala/Java
Hands-on experience with big data technologies such as Hadoop, Hive, and HBase
Proficiency in NoSQL data stores, with experience in Elasticsearch or similar technologies
Proven track record of architecting and optimizing large-scale data pipelines, ETL workflows, and data infrastructure
Familiarity with workflow orchestration tools like Apache NiFi, Airflow
Ability to mentor and guide data engineering teams while driving technical strategy and best practices
We are looking for a TechLead Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is a strategic thinker and hands-on technical leader, passionate about data architecture, performance optimization, and cloud-based data engineering. They should be self-directed, proactive, and comfortable driving data strategy, ensuring our infrastructure meets evolving business needs. You will work closely with software developers, database architects, data analysts, and data scientists to ensure a consistent, scalable, and high-performance data ecosystem across multiple teams, systems, and products.
Main Tasks And Responsibilities
Design and drive the development of scalable, high-performance data pipeline architectures, ensuring optimal data processing, transformation, and storage solutions
Assemble large, complete data sets that meet functional / non-functional business requirements
Lead the design and optimization of data infrastructure, leveraging modern data technologies to ensure scalability, reliability, and efficiency
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, performance, etc.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, revenue management, operational efficiencies, and other key business performance metrics
Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and their data infrastructure needs support
Keep our data separated and secure across national boundaries through multiple data centers and AWS regions
Create data tools for analytics and data scientist team members that assist them in building and optimizing our offerings
Work with data and analytics experts to strive for greater functionality in our data systems
Act as a technical advisor to engineering, product, and executive teams, translating business requirements into scalable data solutions
Education, Skills And Experience
MUST HAVE:
7+ years of experience in data engineering
1+ year in a lead or architect capacity designing and implementing scalable data solutions
Extensive experience working with relational databases and data warehouses, including BigQuery, PostgreSQL, Microsoft SQL Server, Oracle, etc.
Proficient in cloud technologies such as AWS/GCP/Azure, with flexibility to work with any cloud platform
Expertise in real-time and batch data processing using Spark/Kafka Streaming
Experience with programming and scripting languages: Python/Scala/Java
Hands-on experience with big data technologies such as Hadoop, Hive, and HBase
Proficiency in NoSQL data stores, with experience in Elasticsearch or similar technologies
Proven track record of architecting and optimizing large-scale data pipelines, ETL workflows, and data infrastructure
Familiarity with workflow orchestration tools like Apache NiFi, Airflow
Ability to mentor and guide data engineering teams while driving technical strategy and best practices
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