Responsibilities

Job Description:

We’re looking for a Data Engineer with strong Python and SQL skills to build reliable data pipelines that convert semi structured data from ES URLs into clean| analytics ready datasets. You’ll work locally (Python DBeaver SQLite Postgres Dremio)| establish DB connections| flatten JSONES topics into structured tables| and enable downstream reporting in Power BI for business users.

Key Responsibilities

Data Ingestion Transformation Fetch semi structured data from ES URLs Apis (e.g.,| JSON Elasticsearch topics).Flatten| normalize| and model data into structured tables for analytics.

Build reproducible ETLELT workflows in Python (pandas| requests| SQLAlchemy).

Database EngineeringCreate and maintain schemas in SQLite| Postgres| and Dremio.

Configure and manage local DB connections via DBeaver optimize queries and indexes.

Implement data partitioning| incremental loads| and performance tuning.

Data Quality Governance

Establish validation rules| deduplication| and anomaly checks.

Version datasets| maintain data lineage| and document data contract metadata.

Ensure secure handling of credentials| tokens| and endpoints.

Use Git for version control maintain code reviews| unit tests| and CI checks.

Write clear technical documentation and runbooks support adhoc data requests.

Required Skills

Experience Python for Data Science Engineering pandas| NumPy| requests| SQL Alchemy JSON handling and API integration.

SQL advanced proficiency with SQLite| Postgres| and querying via Dremio.

Data Modeling dimensional normalized models handling nested semi structured data.

Tools DBeaver (DB connections)| Power BI (data prep for reporting).Pipelines ETLELT design| performance optimization| error handling| logging.

Collaboration strong communication with business stakeholders’ requirements to delivery

Requirements

Skills: Digital : Python~PostgreSQL~Digital : Microsoft Power BI

Experience Required: 8-10