Senior Data Engineer handling data engineering responsibilities in hybrid setting for banking industry. Collaborating with cross - functional teams and maintaining data quality in Azure environments.
About the role
- Data Engineer developing sustainable data assets for machine learning and analytics solutions. Collaborating with teams and using modern technologies in a hybrid work setting.
Responsibilities
- Participate in developing high quality, scalable software modules for next generation analytics solution suite
- Engage in activities with cross-functional IT unit stakeholders (e.g., database, operations, telecommunications, technical support, etc.)
- Formulates logical statements of business problems and devises, tests and implements efficient, cost-effective application program solutions
- Identify and validate internal and external data sources for availability and quality
- Work with SMEs to describe and understand data lineage and suitability for a use case
- Create data assets and build data pipelines that align to modern software development principles for further analytical consumption
- Perform data analysis to ensure quality of data assets
- Perform preliminary exploratory analysis to evaluate nulls, duplicates and other issues with data sources
- Assist in developing code that enables real-time solutions to be ingested into front-end systems and platforms
- Produce code artifacts and documentation using GitHub for reproducible results and hand-off to other data science teams.
Requirements
- 2+ years of relevant experience recommended
- Bachelor’s degree in Computer Science, Engineering, IT, Management Information Systems, or a related discipline
- Experience in Python and SQL
- Experience in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON
- Experience in ETL concerning metadata management and data validation
- Experience in Unix and Git
- Experience in Automation tools (Autosys, Cron, Airflow, etc.)
- Exposure to AWS or GCP services a plus
- Experience with Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus
- Experience with ELT tools (i.e. DBT, Talend) a plus
- Able to communicate effectively with both technical and non-technical teams
- Able to translate complex technical topics into business solutions and strategies
- Candidate must be authorized to work in the US without company sponsorship.
Benefits
- Other rewards may include short-term or annual bonuses
- long-term incentives
- on-the-spot recognition
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Management professional at Kyndryl involved in creating innovative data solutions and ensuring the seamless operation of complex data systems. Collaborating with teams to transform requirements into scalable database solutions.
Software Engineer designing and developing scalable data processing applications on cloud infrastructure for Thomson Reuters. Collaborating with Data Analysts on AI - enabled solutions for data management and insight generation.
Manager of Data Platform overseeing AWS cloud infrastructure and Snowflake data warehouses for Thomson Reuters. Leading the design and implementation of data processing applications in a hybrid role located in Bengaluru.
Senior Data Engineer designing scalable data pipelines and solutions for Enterprise Data Lake at Thomson Reuters. Collaborating across teams to ensure efficient data ingestion and accessibility.
Senior Data Engineer at Technis developing scalable data pipelines and solutions for innovative connected spaces products. Collaborating within a cross - functional team to deliver high - quality data - driven outcomes.
Architect leading initiatives in data platform engineering at F5, solving challenges in unstructured data and enhancing governance frameworks.
Data Architect designing and implementing data architectures supporting analytics and ML for federal clients. Collaborating with teams to translate mission needs into robust data solutions.
IT Data Engineer developing data pipelines and integrations for Scanfil Group's global IT organization. Collaborating across teams to enhance data solutions and reporting capabilities.
Data Engineer developing Azure data solutions at PwC New Zealand. Responsibilities include data quality monitoring, pipeline development, and collaboration with stakeholders in a supportive environment.