Data Engineer
Gurgaon (Gurgaon) IT development
Job description
Job Summary:
The Data Engineer will join a growing team of analytics experts responsible for expanding and optimizing data, data infrastructure, processing and wrangling.
The position will gather andcleanse data, understands the meaning of datasets and dataset compatibility, integrates data and implements business rules
The Data Engineer will support data scientists, product managers and analysts on data initiatives and will ensure optimal data delivery is consistent across projects.
They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our data infrastructure to support our next generation of products, services and data initiatives.
The outputs of this position leads to insights that support strategic decision-making, along with ideas to automate, innovate, and enhance the measurement and reporting process.
Essential functions of the job:
(Identify and describe the primary duties and responsibilities. Assume that the reader does not know the role or purpose of the job)
· Assemble, gather and cleanse data sets that meet business requirements.
· Queries and/or integrates data by using SQL, SQL-like, ELT or ETL skills tools and techniques.
· Creates data models by delivering calculations, aggregations and derivations from input data.
· Implements business rules that are required to meet business needs
· Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
· Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
· Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
· Design, develop and manage analytic dashboards and new reports
· Analyze, visualize, and provide analytics on data captured daily to build reporting solutions to support various knowledge initiatives
· Work with stakeholders to assist with data-related technical issues and support data and infrastructure needs.
· Drives data accuracy, quality and integrity ensuring compliance with data governance.
· Create data tools for analytics and data scientist team members that assist them in building and optimizing products.
· Work with data and analytics experts to strive for greater functionality in our data systems.
Analytical Responsibilities:
Database development
· RDBMS Database and data processing development (and design)
· Data source analysis to refine code / application of pattern and exceptions
· Catering for data scenarios and failures
· Unit testing with dev / test / live data
Data wrangling
· File, column store, object store and data processing development (and design)
· Data source analysis to refine code / application of pattern and exceptions
· Catering for data scenarios and failures
· Unit testing with dev / test / live data
Test analysis
· Test scenario and case preparation and execution
· Data querying construction and execution
· Testing framework development and configuration
· Defect logging and management
Technical Skill Requirements:
· Strong technical analytics expertise. Good knowledge of data analytics architectures and standards, including data warehouses, master data management, ETL, OLAP, data modelling techniques, meta data management, data quality management, Hadoop, advanced analytics, reporting and self-service BI ;
· Experience in data manipulation using Python, machine learning, Alteryx desirable
Supervision Responsibilities:
· Works with a geographically dispersed team, highly self-motivated, able to work independently
· Ability to complete multiple medium-sized projects and work with project teams
· Directs junior team members
· Able to meet deadlines independently
Other Requirements:
(Is overtime regularly required? Are there times of year that vacation may not be taken? Is frequent travel involved? How much? Are there physical requirements outside of those expected in a normal office environment? Any other miscellaneous points about the job that should be made known?)
Job Requirements:
Education:
· Bachelor degree in computer science or computer engineering
Experience:
· 5 – 7 years of relevant experience in the field of Data Analytics
· 2 years minimum of relevant experience in a professional data management (ETL, manipulation) role
· Ideally, experience in knowledge measurement and analytics program in large organization an advantage
Certification Requirements:
· Project management certification desirable
Job Summary:
The Data Engineer will join a growing team of analytics experts responsible for expanding and optimizing data, data infrastructure, processing and wrangling.
The position will gather andcleanse data, understands the meaning of datasets and dataset compatibility, integrates data and implements business rules
The Data Engineer will support data scientists, product managers and analysts on data initiatives and will ensure optimal data delivery is consistent across projects.
They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our data infrastructure to support our next generation of products, services and data initiatives.
The outputs of this position leads to insights that support strategic decision-making, along with ideas to automate, innovate, and enhance the measurement and reporting process.
Essential functions of the job:
(Identify and describe the primary duties and responsibilities. Assume that the reader does not know the role or purpose of the job)
· Assemble, gather and cleanse data sets that meet business requirements.
· Queries and/or integrates data by using SQL, SQL-like, ELT or ETL skills tools and techniques.
· Creates data models by delivering calculations, aggregations and derivations from input data.
· Implements business rules that are required to meet business needs
· Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
· Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
· Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
· Design, develop and manage analytic dashboards and new reports
· Analyze, visualize, and provide analytics on data captured daily to build reporting solutions to support various knowledge initiatives
· Work with stakeholders to assist with data-related technical issues and support data and infrastructure needs.
· Drives data accuracy, quality and integrity ensuring compliance with data governance.
· Create data tools for analytics and data scientist team members that assist them in building and optimizing products.
· Work with data and analytics experts to strive for greater functionality in our data systems.
Analytical Responsibilities:
Database development
· RDBMS Database and data processing development (and design)
· Data source analysis to refine code / application of pattern and exceptions
· Catering for data scenarios and failures
· Unit testing with dev / test / live data
Data wrangling
· File, column store, object store and data processing development (and design)
· Data source analysis to refine code / application of pattern and exceptions
· Catering for data scenarios and failures
· Unit testing with dev / test / live data
Test analysis
· Test scenario and case preparation and execution
· Data querying construction and execution
· Testing framework development and configuration
· Defect logging and management
Technical Skill Requirements:
· Strong technical analytics expertise. Good knowledge of data analytics architectures and standards, including data warehouses, master data management, ETL, OLAP, data modelling techniques, meta data management, data quality management, Hadoop, advanced analytics, reporting and self-service BI ;
· Experience in data manipulation using Python, machine learning, Alteryx desirable
Supervision Responsibilities:
· Works with a geographically dispersed team, highly self-motivated, able to work independently
· Ability to complete multiple medium-sized projects and work with project teams
· Directs junior team members
· Able to meet deadlines independently
Other Requirements:
(Is overtime regularly required? Are there times of year that vacation may not be taken? Is frequent travel involved? How much? Are there physical requirements outside of those expected in a normal office environment? Any other miscellaneous points about the job that should be made known?)
Job Requirements:
Education:
· Bachelor degree in computer science or computer engineering
Experience:
· 5 – 7 years of relevant experience in the field of Data Analytics
· 2 years minimum of relevant experience in a professional data management (ETL, manipulation) role
· Ideally, experience in knowledge measurement and analytics program in large organization an advantage
Certification Requirements:
· Project management certification desirable