Data Engineer

Job Title: Data Engineering

Job Location: Hyderabad, India

Worksite: Onsite (100%)

About WCT:

WaferWire Technology Solutions (WCT) specializes in delivering comprehensive Cloud, Data and AI solutions through Microsoft's technology stack. Our services include Strategic Consulting, Data/AI Estate Modernization, and Cloud Adoption Strategy. We excel in Solution Design encompassing Application, Data, and AI Modernization, as well as Infrastructure Planning and Migrations. Our Operational Readiness services ensure seamless DevOps, ML Ops, AI Ops, and Sec Ops implementation. We focus on Implementation and Deployment of modern applications, continuous Performance Optimization, and future-ready innovations in AI, ML, and security enhancements. Delivering from Redmond-WA, USA, Guadalajara, Mexico and Hyderabad, India, our scalable solutions cater precisely to diverse business requirements and multiple time zones (US time zone alignment).

Responsibilities:

Python + Data Engineering

Strong Python for ETL/ELT: requests, pandas, pyarrow, retry/backoff, logging, config management

API ingestion patterns: OAuth/keys, pagination, delta tokens, throttling, idempotency

File ingestion: CSV/JSON/Parquet handling; schema inference vs explicit schema; large file chunking/streaming

Microsoft Fabric Warehouse / Data Loading

Understanding of Fabric ingestion approaches such as pipelines/copy jobs into Warehouse; ability to implement full/incremental patterns.

SQL/T-SQL for warehouse DDL/DML, loading strategies, and validation queries.

Data Warehouse Architecture (Scalable)

Dimensional modeling (facts/dimensions), star schema, SCD handling

Data lifecycle layers: raw/staging/curated; metadata-driven pipelines

Scalability concepts: parallelism, partitioning strategy, incremental loads, late-arriving data, CDC design

Understanding modern DW engine traits discussed for Fabric DW (e.g., compute/storage separation, optimized for open formats).

Observability + Reliability

Monitoring: job metrics, failure handling, alerting

Data quality checks: row counts, null checks, referential integrity, schema drift detection

CI/CD basics and version control best practices (often expected in Fabric/Azure data engineer roles).

Required Qualifications:

35+ years building data pipelines and data warehouse solutions (common baseline in Azure/Fabric data engineering JDs).

Strong SQL + Python, plus hands-on delivery on a modern analytics platform.

Good to Have (Optional):

Familiarity with broader Fabric ecosystem (Lakehouse, semantic models, governance patterns)

DP-600 (Fabric) / Azure data certifications (commonly preferred in similar JDs)

Spark/PySpark experience for large-scale transformations (useful where ingestion requires heavy processing)

Equal Employment Opportunity Declaration:

WCT is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic

information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.