Data Engineer

Job Title: Data Engineer 

Location: Hyderabad, Onsite 

Type : Full Time

Role & responsibilities

Key Responsibilities:
• Data Pipeline Development: Design, develop, and manage robust data pipelines to collect, transform, and load (ETL) data from various sources into scalable data storage solutions.
• Data Integration: Collaborate with AI engineers, data scientists, and business stakeholders to ensure seamless data integration across different platforms and applications.
• Cloud Data Platforms: Work with cloud platforms like AWS, Azure, or Google Cloud to set up and maintain cloud-based data storage and analytics solutions.
• Data Architecture: Design and implement efficient data architectures to support large-scale data ingestion, storage, and processing needs for AI/ML models.
• Real-Time Data Access: Optimize data flows to enable real-time data access and insights, ensuring low-latency data availability for AI-powered solutions.
• Data Quality & Monitoring: Implement data quality controls, data validation, and monitoring mechanisms to ensure clean, consistent, and reliable data for AI models and decision-making.
• ETL Optimization: Continuously improve ETL processes for performance, scalability, and data integrity by leveraging automation, parallelism, and modern tools.
• Collaboration: Work closely with cross-functional teams to understand data needs, translate them into engineering solutions, and ensure data accessibility and scalability.
Qualifications:
• Bachelors or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 3+ years of experience as a Data Engineer, building and managing scalable data pipelines, ETL processes, and data infrastructure.
• Proficiency in SQL, Python, or similar programming languages for data manipulation and pipeline automation.
• Experience with cloud platforms like AWS, Azure, or Google Cloud, and their data services (e.g., S3, Redshift, BigQuery, or Azure Data Lake).
• Strong knowledge of ETL tools (e.g., Apache Airflow, Talend, or dbt) and data processing frameworks like Spark or Hadoop.
• Hands-on experience in designing data architectures that support AI/ML workflows and real-time data solutions.
• Solid understanding of data warehousing, data lakes, and database design principles.
• Experience with CI/CD pipelines for data engineering and data workflow automation.
Preferred Skills:
• Experience with containerization (Docker, Kubernetes) for data pipeline deployment and scalability.
• Familiarity with modern data platforms like Snowflake, Databricks, or similar.
• Knowledge of stream processing tools like Kafka or AWS Kinesis for real-time data processing.
• Experience with data governance and data security best practices.
• Certification in AWS Certified Data Analytics, Azure Data Engineer Associate, or Google Cloud Data Engineer is a plus.

Preferred candidate profile

Perks and benefits