Urgent Opening Data Engineer

Overview

We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate will have strong expertise in data integration, ETL processes, and cloud data platforms, ensuring efficient collection, transformation, and storage of data across multiple sources. This role plays a key part in enabling data-driven decision-making and supporting analytics and machine learning initiatives.

About CoreOps.AI

CoreOps.AI is a next-generation technology company focused on building AI-powered, scalable enterprise solutions. We combine intelligent automation and data-driven strategies to help businesses achieve modernization and efficiency.

Key Responsibilities

• Design, build, and maintain scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources into data storage systems.
• Develop and implement data models and schemas to organize and structure data for optimal storage, retrieval, and analysis.
• Integrate data from different sources and formats, ensuring consistency, accuracy, and reliability across the data ecosystem.
• Implement processes and standards to ensure data quality, integrity, and consistency, including data validation, cleansing, and error handling.
• Optimize data pipelines, queries, and processes for improved performance, scalability, and efficiency, addressing bottlenecks and enhancing overall system performance.
• Establish and enforce data governance policies and security measures to protect sensitive data, ensure compliance with regulatory requirements, and mitigate risks related to data privacy and security.
• Collaborate with cross-functional teams, including SAP, application dev team, data scientists, analysts, and stakeholders, to understand data requirements, provide technical expertise, and support data-driven decision making.
• Document data engineering processes, workflows, and best practices, and provide training and support to users to ensure effective utilization of data infrastructure and tools.
• Stay updated with emerging technologies, trends, and best practices in data engineering, and actively seek opportunities to enhance skills and knowledge through training, certifications, and professional development initiatives.
• Establish and enforce data governance standards implement best practices for data privacy and protection in AI application.
  
  

Bachelor’s/Master’s degree in computer science, data science, mathematics or a related field.

• At least 4–6 years’ experience in data engineering.
  
  

Additional Information

Preferred Skills

• Strong programming skills in languages such as Python, Java or SQL for data manipulation, scripting, and automation tasks.
• Experience with data warehousing concepts and technologies (e.g., SQL databases, NoSQL databases, data lakes) and expertise in database design, optimization, and administration.
• Familiarity with ETL (Extract, Transform, Load) tools and frameworks such as Apache Spark, Apache Beam, Informatica, Talend, or Apache NiFi for building and managing data pipelines.
• Knowledge of big data platforms and frameworks like Hadoop, Apache Kafka, Apache HBase, Apache Hive, or Apache Flink for processing and analyzing large volumes of data.
• Proficiency in data modeling techniques and tools (e.g., ER diagrams, dimensional modeling) to design efficient and scalable data schemas and structures.
• Experience with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure, and proficiency in using cloud-based services for data storage, processing, and analytics.
• Familiarity with version control systems like Git for managing codebase, collaborating with team members, and tracking changes in data pipelines and workflows.
• Knowledge of data visualization tools and libraries (e.g., Tableau, Power BI, matplotlib, seaborn) to create insightful visualizations and dashboards for data analysis and reporting.
• Has worked on providing end to end solution.
• Great communication and collaboration skills.
• Self-starter, Entrepreneurial, result oriented mindset.
• Excellent communication, negotiation, and interpersonal skills.
  
  

A competitive compensation package, including base salary, performance-based commissions, and benefits. Opportunities for professional growth, training, and career advancement in a dynamic and rapidly evolving industry. Collaborative and inclusive work culture that values teamwork, innovation, and a strong commitment to customer success.