Job Summary
We are looking for a Data Engineer responsible for data analysis, validation, cleansing, collection, and reporting. The role involves extracting and analyzing data from various sources (databases, manual files, and external systems), ensuring data quality, and generating both scheduled and ad-hoc reports. The ideal candidate must have strong analytical and organizational skills, expert-level proficiency in MS Excel, and prior experience as a Data Analyst.
Key Responsibilities
- Design, build, and maintain batch or real-time data pipelines in production.
- Maintain and optimize data infrastructure for accurate extraction, transformation, and loading (ETL) from multiple data sources.
- Automate data workflows, including ingestion, aggregation, and ETL processes.
- Prepare raw data in Data Warehouses into consumable datasets for both technical and non-technical stakeholders.
- Collaborate with data scientists and cross-functional teams (sales, marketing, product) to deploy machine learning models in production.
- Build, maintain, and deploy data products for analytics and data science teams on cloud platforms.
- Ensure data privacy, security, compliance, and quality through appropriate controls.
- Design data structures.
- Create service APIs.
- Develop profiling processes.
- Integrate data lake with 3rd-party platforms (e.g., Medallia) and provide service APIs if required.
- Manage data ingestion, including involvement in EDL (data lake platform) and ETL (data transfer).
- Perform data ingestion from PL/SQL to the data lake, validating and comparing data accuracy between both sources.
Requirements:
- 2–4 years of experience as a
Data Engineer
. - Must-have technical skills:
- Azure Data Factory (or similar tools, e.g., AWS Glue).
- Proficiency in
Python
for data analytics. - Experience with
PL/SQL databases
. - Strong English communication skills (written & verbal).
- NEED ASAP Candidate