2+ Automatic Data Processing Jobs in India

MANDATORY:

• Super Quality Data Architect, Data Engineering Manager / Director Profile
• Must have 12+ YOE in Data Engineering roles, with at least 2+ years in a Leadership role
• Must have 7+ YOE in hands-on Tech development with Java (Highly preferred) or Python, Node.JS, GoLang
• Must have strong experience in large data technologies, tools like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto etc.
• Strong expertise in HLD and LLD, to design scalable, maintainable data architectures.
• Must have managed a team of at least 5+ Data Engineers (Read Leadership role in CV)
• Product Companies (Prefers high-scale, data-heavy companies)

PREFERRED:

• Must be from Tier - 1 Colleges, preferred IIT
• Candidates must have spent a minimum 3 yrs in each company.
• Must have recent 4+ YOE with high-growth Product startups, and should have implemented Data Engineering systems from an early stage in the Company

ROLES & RESPONSIBILITIES:

• Lead and mentor a team of data engineers, ensuring high performance and career growth.
• Architect and optimize scalable data infrastructure, ensuring high availability and reliability.
• Drive the development and implementation of data governance frameworks and best practices.
• Work closely with cross-functional teams to define and execute a data roadmap.
• Optimize data processing workflows for performance and cost efficiency.
• Ensure data security, compliance, and quality across all data platforms.
• Foster a culture of innovation and technical excellence within the data team.

IDEAL CANDIDATE:

• 10+ years of experience in software/data engineering, with at least 3+ years in a leadership role.
• Expertise in backend development with programming languages such as Java, PHP, Python, Node.JS, GoLang, JavaScript, HTML, and CSS.
• Proficiency in SQL, Python, and Scala for data processing and analytics.
• Strong understanding of cloud platforms (AWS, GCP, or Azure) and their data services.
• Strong foundation and expertise in HLD and LLD, as well as design patterns, preferably using Spring Boot or Google Guice
• Experience in big data technologies such as Spark, Hadoop, Kafka, and distributed computing frameworks.
• Hands-on experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery
• Deep knowledge of data governance, security, and compliance (GDPR, SOC2, etc.).
• Experience in NoSQL databases like Redis, Cassandra, MongoDB, and TiDB.
• Familiarity with automation and DevOps tools like Jenkins, Ansible, Docker, Kubernetes, Chef, Grafana, and ELK.
• Proven ability to drive technical strategy and align it with business objectives.
• Strong leadership, communication, and stakeholder management skills.

PREFERRED QUALIFICATIONS:

• Experience in machine learning infrastructure or MLOps is a plus.
• Exposure to real-time data processing and analytics.
• Interest in data structures, algorithm analysis and design, multicore programming, and scalable architecture.
• Prior experience in a SaaS or high-growth tech company.

We are seeking a detail-oriented and technically proficient Product Specialist to support and enhance our HR and business data systems. The ideal candidate will have hands-on experience with Excel VBA and Macros, HR Analytics, system migration, and data processing. This role requires a strong analytical mindset, a deep understanding of Excel automation, and the ability to contribute to cross-functional system integration and process improvement initiatives.

Qualifications:

• Bachelor's degree in Information Systems, HR, Business, or a related field.
• 2–5 years of hands-on experience with Excel VBA and Macros development.
• Proficient in HR data analysis and working with HRIS systems (e.g., Workday, SAP SuccessFactors, BambooHR).
• Experience with system migrations, data conversion, and UAT.
• Strong analytical, problem-solving, and organizational skills.
• Familiarity with Power BI, SQL, or Python is a plus.

Key Competencies:

• High attention to detail and accuracy.
• Effective communication with technical and non-technical stakeholders.
• Ability to manage multiple priorities and work under tight deadlines.
• Team player with a continuous improvement mindset.