Job Purpose
As a Data Engineer, you will bring deep technical expertise and act as a subject-matter expert within the team. You will be responsible for the technical configuration, development, integration, and operation of data platforms and products built on our core technology stack.
You will work closely with Product Owners, Product Architects, and cross-functional teams to understand business needs and translate them into robust technical solutions aligned with engineering standards and roadmaps. You will contribute hands-on by implementing new features, writing high-quality code, following agile methodologies, and supporting the team in delivering on time.
You are expected to be a proactive team player - maintaining documentation, raising questions, offering support, and actively participating in team ceremonies. You will also help drive continuous improvement in engineering practices and contribute to delivering high-quality solutions across the full data lifecycle.
Technology Stack
Must Have Strong proficiency in Python and SQL Experience with big data technologies , including MPP and streaming Hands-on experience with cloud platforms (AWS, Azure, or GCP) Experience with data and compute platforms such as Databricks, Big Query, or Snowflake Experience with CI/CD tools and processes (Azure Dev Ops, Jenkins, Git) Familiarity with APIs for data ingestion and extraction Ability to understand high-level design and architecture documents and translate them into development tasks
Nice to Have Experience with Microsoft data stack (Azure Data Factory, Azure Synapse, Databricks, Fabric, Power BI) Data modelling and data architecture experience
ETL pipeline design and optimization
Advanced expertise in Py Spark Logging and monitoring using Azure / Databricks services
Experience with Apache Kafka or similar streaming platforms Exposure to machine learning and AI technologies
Key Responsibilities
Coach and mentor data engineers in designing, developing, and delivering scalable, reliable, and high-performance data solutions
Design, develop, and maintain scalable data pipelines and ETL processes
Monitor and optimize data infrastructure performance, resolving bottlenecks and issues
Drive technical excellence through code reviews, design reviews, testing, and deployment practices
Act as an individual contributor (~60%), engineering software solutions alongside the team
Ensure adherence to coding standards, best practices, and architectural guidelines
Oversee implementation of technical architecture and resolve complex technical challenges
Ensure Dev Sec Ops practices are embedded in daily team operations
Guide development approaches and manage technical debt
Hire, onboard, mentor, and develop engineering talent, fostering a culture of collaboration and continuous improvement
Lead technical discussions with cross-functional teams when required
Represent the data engineering domain in broader technical and architectural discussions
Design and improve processes to enhance delivery efficiency and solution quality
Collaborate with Engineering Manager, Product Owner, Business Analyst, and Scrum Master to align on sprint goals, timelines, and resources
Requirements 4–7 years of experience in Data Engineering Strong hands-on experience with data integration, ETL processes, and data warehousing
In-depth knowledge of the mandatory technology stack
Strong understanding of software engineering principles, coding standards, and modern architectures
Familiarity with data governance and compliance standards
Experience delivering end-to-end Data Ops / Data Engineering projects within a team
Proven ability to guide and mentor engineers with varying experience levels
Experience working across diverse projects, technologies, and systems
Strong problem-solving and decision-making skills
Ability to work independently and take initiative
Excellent collaboration and communication skills
A pragmatic mindset and strong team orientation
A Data Engineer is responsible for designing, building and maintaining large-scale data systems, ensuring data quality and security. They work with data architects, scientists and analysts to integrate and process data from various sources.
Typically, a bachelor's degree in computer science, engineering or a related field is required. Proficiency in programming languages like Java, Python and SQL, as well as experience with big data technologies like Hadoop and Spark, are also essential.
The average salary of a Data Engineer in Hyderabad ranges from 8 to 15 lakhs per annum, depending on experience and skills. Senior roles can command higher salaries, up to 25 lakhs per annum.
Key skills include data analysis, data modeling, data warehousing, ETL tools, cloud computing and machine learning. Proficiency in programming languages, data visualization tools and agile methodologies is also important.
With the increasing demand for data-driven decision making, the career prospects for Data Engineers in Hyderabad are promising. They can move into senior roles like Technical Lead, Data Architect or Director of Engineering, or explore related fields like data science and analytics.
