Client: Publicis Sapient
Position: Data Engineer
Pay Rate: $65/hr on C2C
Visa: USC, GC, EAD -No OPT
Need Retail/Wholesale industry experience.
Job Description:
1. Data Pipeline Development:
Design, develop, and maintain robust data pipelines using Python programming
language to extract data from Snowflake and SAP systems and transform it into
the desired format for the target system.
Implement efficient data ingestion, transformation, and loading processes to
ensure accurate and reliable data transfer between systems.
2. Data Transformation:
Define and implement data transformation rules and logic to clean, filter,
aggregate, and transform data from Snowflake and SAP into the required format
for the target system.
Leverage Python libraries and frameworks such as Pandas, NumPy, or PySpark to
manipulate and process data efficiently during the transformation process.
Ensure data quality and integrity by applying data validation, normalization, and
standardization techniques.
Collaborate with data analysts and business stakeholders to understand data
semantics and requirements for accurate transformations.
3. Data Integration and System Connectivity:
Establish connectivity with Snowflake and SAP systems, extracting data through
APIs, database connectors, or other relevant methods.
Integrate and synchronize data from multiple sources, ensuring data consistency
and coherence.
Collaborate with IT teams to implement secure and efficient data transfer
mechanisms, adhering to data governance and compliance policies.
4. Documentation and Collaboration:
Required Skills and Qualifications:
Strong proficiency in Python programming language.
Experience in building data pipelines and ETL processes.
Familiarity with Snowflake and SAP systems, including data extraction methods (e.g.,
APIs, database connectors).
Knowledge of data transformation techniques and tools.
Proficiency in Python libraries and frameworks for data manipulation (e.g., Pandas,
NumPy, PySpark).
Understanding of database systems and SQL queries.
Experience with data integration and synchronization.
Familiarity with data governance and compliance principles.