Data Engineer/ Senior Data Engineer

Aays; Dehradun; On-site; INR 800,000 - 1,200,000; Full time

Job summary

Aays in India is seeking a Data Engineer at junior to principal level to design, build, and deploy Big Data and Analytics solutions. You will work with partners, architects, CTOs, and product owners to deliver scalable, cloud-native data platforms that enable analytics, AI, and BI.

The role emphasizes communication, problem solving, and mentoring, with opportunities to lead design and delivery depending on experience.

Qualifications

• 3+ years of experience in data engineering or related fields.
• Experience building scalable ETL/ELT pipelines in cloud environments.
• Strong knowledge of data modelling, data integration, and query optimization.
• Excellent communication and collaboration with cross-functional teams.

Responsibilities

• Develop scalable Data Engineering solutions within Big Data cloud environments.
• Build and optimize enterprise-grade ETL/ELT pipelines.
• Work with divergent datasets to support Data Science analytics teams.
• Design Data Architectures using Azure components and Databricks.
• Mentor junior team members and contribute to engineering best practices.

Skills

Python

Apache Spark

SQL

Power BI

Tableau

Git

Data Modelling

Data Transformation

Azure

GCP

ETL/ELT pipelines

Databricks

Cloud Platforms

Education

Bachelor's or Master's in Computer Science/IT/Engineering

Tools

Azure Data Factory

Azure Data Lake

Azure Synapse Analytics

Databricks

GCP

Spark

Git

CI/CD

Job description

Position: Data Engineer (Junior / Senior / Principal)

Desired Experience: 3+ Years

About the Role

As a Data Engineer, you will be a key member of the Data Consulting team, working directly with partners, architects, CTOs, product owners, and senior client stakeholders to design, build, and implement Big Data and Analytics solutions. You will contribute to the development of scalable, cloud-native data platforms that enable advanced analytics, AI, and business intelligence. Communication and organizational skills are key for this position, along with a strong problem-solving attitude. Depending on your experience level, you will contribute to or lead the design, implementation, optimization, and delivery of enterprise-scale Data Engineering solutions.

What is in it for you?

• Opportunity to work with a world-class team of business consultants, architects, and engineers solving some of the most complex business problems using Data Engineering, Analytics, and AI.
• Exposure to enterprise-scale Big Data and Cloud projects across multiple industries.
• Fast-track career growth in a highly entrepreneurial work environment.
• Opportunity to work with cutting-edge Data Engineering and Cloud technologies.
• Best-in-industry remuneration package.

Essential Technical Skills

• Strong technical expertise in modern Big Data technologies including Python, Apache Spark, Hadoop, Clojure, Git, SQL, and Databricks.
• Hands-on experience with Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, and modern cloud-based data platforms.
• Experience working with Azure and/or Google Cloud Platform (GCP).
• Experience with cloud infrastructure, containerization, and microservices.
• Hands-on experience in designing and developing scalable ETL/ELT pipelines.
• Experience working with divergent datasets supporting Data Science and Data Analytics teams.
• Strong understanding of Data Integration, Data Transformation, Data Modelling, Query Optimization, and Complexity Analysis.
• Experience with visualization tools including Power BI and Tableau.
• Practical implementation experience in modern Data Engineering technologies is essential.

Desirable Skills

• Experience working in Agile environments.
• Knowledge of Agile methodologies such as Scrum.
• Experience working with development teams and Product Owners to understand business requirements.
• Exposure to enterprise-scale cloud-based Data Engineering solutions.
• Experience with CI/CD pipelines and DevOps practices is an advantage.
• Microsoft Azure, Databricks, GCP, or other relevant certifications will be preferred.

Key Responsibilities

• Develop scalable Data Engineering solutions within Big Data Azure and/or other cloud environments.
• Build, develop, and optimize enterprise-grade ETL/ELT pipelines.
• Work with divergent datasets to support the requirements of the Data Science and Data Analytics teams.
• Build and design Data Architectures using Azure Data Factory, Databricks, Azure Data Lake, Azure Synapse, and other cloud technologies.
• Perform Data Integration, Data Transformation, and Data Modelling activities.
• Perform data mapping activities to define source data, target data, and transformation logic.
• Collaborate with CTOs, Product Owners, Architects, and Operations teams to deliver engineering roadmaps, including upgrades, technical refreshes, and new platform versions.
• Assist the Data Analytics team in developing KPIs, dashboards, and reporting solutions using Power BI and Tableau.
• Optimize SQL queries, Spark workloads, and overall data platform performance.
• Maintain technical documentation, solution documentation, and knowledge repositories.
• Research, evaluate, and recommend emerging database technologies, products, services, and engineering best practices.
• Collaborate effectively with cross-functional teams to deliver high-quality Data Engineering solutions.
• Mentor junior team members and contribute to engineering best practices based on experience level.

Essential Personal Traits

• Excellent communication skills in English and stakeholder management skills.
• Strong analytical thinking and problem-solving abilities.
• Ability to work independently while collaborating effectively with remote and distributed teams.
• Timely communication and escalation of project risks, issues, and dependencies.
• Strong organizational and planning skills.
• Curiosity to learn, adapt, and apply emerging technologies to solve business problems.
• Strong ownership mindset with a commitment to delivering high‑quality engineering solutions.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in Azure, Databricks, GCP, Cloud Technologies, or Data Engineering are preferred.