Data Engineer - Python/SQL

Job Description - Data Engineer :

Job Title : Data Engineer

Employment Type : Full-Time

Experience : 7+ Years

Work Mode : Hybrid

Locations : Pune | Bangalore | Mumbai | Noida

Shift Timing : 2 : 00 PM 11 : 00 PM IST

Job Summary :

We are looking for a highly skilled Data Engineer with 7+ years of experience in designing, developing, and implementing enterprise-scale data solutions. The ideal candidate should have strong expertise in Python, SQL, PySpark, and cloud platforms such as AWS or Azure. The candidate will be responsible for building scalable data pipelines, optimizing data processing frameworks, and delivering high-quality data solutions to support business intelligence and analytics initiatives. This role requires excellent analytical skills, stakeholder management, and experience working with global cross-functional teams.

Key Responsibilities :

- Design, develop, and maintain scalable and reliable data pipelines for structured and unstructured data.

- Build enterprise-grade ETL/ELT solutions for data ingestion, transformation, and integration.

- Develop cloud-native data solutions using AWS or Microsoft Azure.

- Create high-performance data processing applications using Python and PySpark.

- Write complex and optimized SQL queries for data extraction, transformation, and reporting.

- Develop scalable data models for business intelligence and analytics.

- Implement and maintain DataOps, DevOps, and DevSecOps best practices across the data engineering lifecycle.

- Collaborate with business stakeholders to gather, analyze, and understand data requirements.

- Ensure data quality, integrity, governance, and security across all data platforms.

- Monitor, troubleshoot, and optimize existing data pipelines for performance and scalability.

- Support cloud migration and modernization initiatives.

- Work closely with BI Developers, Data Analysts, Data Scientists, and business users to deliver end-to-end data solutions.

- Participate in code reviews, technical discussions, and architecture design sessions.

- Prepare technical documentation and support production deployments.

- Collaborate with cross-functional teams across multiple regions and time zones.

Mandatory Skills :

1. Programming Languages :

- Python

- SQL

- PySpark

2. Cloud Platforms :

- Amazon Web Services (AWS) or Microsoft Azure

3. Data Engineering :

- ETL / ELT Development

- Data Pipeline Development

- Data Integration

- Data Warehousing

- Data Modeling

- Data Transformation

- Data Validation

- Data Quality Management

4. Cloud BI & Analytics :

- Cloud BI Solutions

- Data Lake Architecture

- Business Intelligence

- Reporting Solutions

5. DevOps Practices :

- DevOps

- DataOps

- DevSecOps

- CI/CD Pipelines

- Git

6. Database Technologies :

- SQL Server

- PostgreSQL

- MySQL

- Snowflake (Preferred)

- Amazon Redshift (Preferred)

- Azure Synapse (Preferred)

7. Big Data Technologies (Preferred) :

- Apache Spark

- Hadoop

- Kafka

- Databricks

Roles & Responsibilities :

- Deliver enterprise data engineering solutions from design through production deployment.

- Build efficient and reusable data pipelines.

- Optimize query performance and data processing workloads.

- Develop cloud-based analytical solutions.

- Automate data workflows and deployment processes.

- Work with business teams to convert functional requirements into technical solutions.

- Ensure compliance with enterprise data governance standards.

- Troubleshoot production issues and provide timely resolutions.

- Mentor junior team members and promote engineering best practices.

Required Experience :

- 7+ years of overall Data Engineering experience.

- Minimum 6+ years delivering enterprise Data Solutions.

- Minimum 3+ years working with Cloud BI solutions using AWS or Azure.

- Strong hands-on experience in Python, SQL, and PySpark.

- Experience building enterprise-scale ETL/ELT pipelines.

- Experience working with cloud-based data platforms.

- Strong understanding of modern data architecture and engineering principles.

- Experience implementing DevOps, DataOps, and DevSecOps practices.

- Experience working with distributed teams across multiple regions and time zones.

Preferred Skills :

- Experience with Snowflake, Databricks, or Azure Synapse.

- Knowledge of Apache Airflow or similar workflow orchestration tools.

- Familiarity with Docker and Kubernetes.

- Experience with Agile/Scrum methodologies.

- Knowledge of Data Governance and Data Security best practices.

- Exposure to AI/ML data pipelines is an added advantage.

Soft Skills :

- Excellent communication and presentation skills.

- Strong analytical and problem-solving abilities.

- Excellent stakeholder management skills.

- Ability to gather and analyze business requirements.

- Strong collaboration and teamwork skills.

- Ability to work independently in a fast-paced environment.

- Excellent time management and multitasking abilities.

- Experience working with global clients and cross-functional teams.

Preferred Candidate Profile :

- Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.

- Passion for solving complex data challenges.

- Strong ownership and accountability.

- Ability to learn and adapt to new technologies quickly.

- Experience delivering enterprise-scale cloud data solutions.

- Strong focus on quality, performance, and scalability.

(ref:hirist.tech)