The company is looking to solve business problems by leveraging data through efficient data extraction, transformation, and loading processes, designing complex data models, and implementing robust data integration and quality solutions.
Requirements
- 6+ years’ experience in developing large scale data pipelines in a cloud/on-prem environment.
- Highly Proficient in any or more of market leading ETL tools like Informatica, DataStage, SSIS, Talend, etc.
- Deep knowledge in Data warehouse/Data Mart architecture and modelling
- Define and develop data ingest, validation, and transform pipelines.
- Deep knowledge of distributed data processing and storage
- Deep knowledge of working with structured, unstructured, and semi structured data
- Working experience needed with ETL/ELT patterns
- Extensive experience in the application of analytics, insights and data mining to commercial “real-world” problems
- Technical experience in any one programming language preferably, Java, .Net or Python
Responsibilities
- Leads the delivery processes of data extraction, transformation, and load from disparate sources into a form that is consumable by analytics processes, for projects with moderate complexity, using strong technical capabilities and sense of database performance
- Designs, develops and produces data models of relatively high complexity, leveraging a sound understanding of data modelling standards to suggest the right model depending on the requirement
- Designs an efficient way of processing high volumes of data where a group of transactions is collected over a period (Batch Processing)
- Designs and implements models, capabilities, and solutions to manage data within the enterprise (structured and unstructured, data archiving principles, data warehousing, data sourcing, etc.). This includes the data models, storage requirements and migration of data from one system to another (Data Integration)
- Reviews (profiles) a data set to establish its quality against a defined set of parameters and to highlight data where corrective action (cleansing) is required to remediate the data (Data Quality, Profiling and Cleansing)
- Discovers, integrates, and ingests all available data from the machines that produce it, as fast as it is produced, in any format, and at any quality (Stream Systems)
- Understands the difference between on-prem and cloud-based data integration technologies.
Other
- Excellent interpersonal skills to build network with variety of department across business to understand data and deliver business value and may interface and communicate with program teams, management and stakeholders as required to deliver small to medium-sized projects
- Opportunity to join a global team to do meaningful work that contributes to global strategy and individual development
- An outstanding opportunity to re-imagine, redesign, and apply technology to add value to the business and operations
- Gives an opportunity to showcase candidates’ strong analytical skills and problem-solving ability
- Learning & Growth opportunities in cloud and Big data engineering spaces
- BE/Btech in Computer Science, Engineering or relevant field
