Data Tech Lead
hace 2 semanas
Currently, we are seeking a** Teach Dat Lead**:
**What You Will B**e Doing**:
- Identifying data sources, both internal and external and working out a plan for data management that is aligned with organizational data strategy.
- Developing and implementing an overall organizational data strategy that is in line with business processes. The strategy includes data model designs, database development standards, implementation and management of data warehouses and data analytics systems.
- Identifying data sources, both internal and external, and working out a plan for data management that is aligned with organizational data strategy.
- Coordinating and collaborating with cross-functional teams, stakeholders, and vendors for the smooth functioning of the enterprise data system.
- Planning and execution of big data solutions using technologies such as Hadoop. In fact, the big data architect roles and responsibilities entail the complete life-cycle management of a Hadoop Solution.
**Your Profile Includes**:
- Knowledge of programming languages Python, Dyango, Airflow.
- Generate the data file using the client's Data Team infrastructure on ingestion
- Load the generate date file in the above step into internal format using Data Pipeline Infrastructure
**Work Breakdown**
- Ingestion: Implement the data pipeline from Fivetran source (Postgres Aurora) to internal file generation. The files are as below:
- First info file
- Remaining info files
- Stats files
- Load: Implement the data pipeline from the generated internal file during ingestion to loading into the client environment's datastore. Below are the files that need to be loaded.
- Data source tables and related infrastructure preparation
- First info file
- Remaining info files
- Stats files
- Feature implemented as per requirements and as per Engineering Excellence guidelines.
- The implementation must follow documented playbook for integrating media sources through Fivetran. This includes
- Using the common base classes used by the existing integrations
- Using Tracer's common utility classes for basic functionalities
- All code must be submitted as GitHub pull requests and reviewed by a member of the Data team
- All code must include full unit test coverage
- All code must include integration tests
- All code must pass CICD pipeline, including python linting, black formatting, and 100% test coverage for functional code using patterns. Any exception to this will have to be approved by the client team.
- Of data mining, machine learning skills, visualization, systems development, including system development life cycle, project management approaches and requirements, design and testing techniques.
- Proficiency in data modeling and design, including SQL development and database administration.
- Ability to implement common data management and reporting technologies, as well as the basics of columnar and NoSQL databases, data visualization, unstructured data, and predictive analytics.
- Understanding of predictive modeling, NLP and text analysis, Machine Learning (Desirable).
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