Job Description

We are looking for a skilled and motivated

Data Engineer

to design, build, and maintain scalable

data pipelines

and

data models

to support analytics, reporting, and machine learning initiatives. You will play a key role in transforming raw data into structured and reliable datasets that power business decisions.

The ideal candidate has strong experience in data architecture, pipeline orchestration, and dimensional modeling, and is comfortable working in a fast-paced, data-driven environment.

Key Responsibilities:1. Data Pipeline Development

Design, build, and maintain reliable, scalable, and efficient ETL/ELT data pipelines. Ingest data from various sources (APIs, databases, streaming platforms, etc.). Monitor and troubleshoot data flows to ensure data integrity and timeliness.

2. Data Modeling

Design and implement data models (e.g., star/snowflake schema) for analytics and reporting. Build and maintain a high-quality data warehouse or data lake architecture. Collaborate with analysts, data scientists, and product teams to define data requirements and deliver well-structured datasets.

3. Data Governance & Quality

Implement and maintain data validation, quality checks, and documentation. Establish and enforce best practices for data accuracy, consistency, and lineage.

4. Collaboration & Support

Work closely with data analysts, scientists, and software engineers to support data needs across the organization. Provide technical guidance on data infrastructure and architecture decisions. Document data models, data dictionaries, and pipeline workflows.

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field. 5+ years of experience in data engineering, with hands-on work in data modeling and building pipelines. Proficiency with SQL and at least one programming language (Python, Scala, or Java). Experience with modern data stack tools (e.g., dbt, Airflow, Fivetran, Snowflake, BigQuery, Redshift, Databricks, etc.). Strong understanding of relational and non-relational databases. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with CI/CD for data workflows and version control tools (Git).

Nice to Have:

Experience with streaming technologies (Kafka, Kinesis, Spark Streaming). Knowledge of data security and compliance (GDPR, HIPAA, etc.). Exposure to ML pipelines or MLOps workflows. Familiarity with business intelligence tools (Looker, Tableau, Power BI).
Job Type: Full-time

Pay: ₹470,047.17 - ₹1,816,443.00 per year

Work Location: In person