Vice President

Description :Mandatory :Super Quality Data Architect, Data Engineering Manager / Director (Experience 1) : - Must have total 10+ YOE of which 6+ YOE in Data Engineering roles, with at least 2+ years in a Leadership (Experience 2) : - Must have 7+ YOE in hands-on Tech development with Java (Highly preferred) or Python, Node.JS, (Experience 3) : - Must have strong experience in large data technologies, tools like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto (Experience 4) : - Strong expertise in HLD and LLD, to design scalable, maintainable data (Team Management) : - Must have managed a team of atleast 5+ Data Engineers (Read Leadership role in (Company) : - Product Companies (Prefers high-scale, data-heavy (Education) : - Must be from Tier - 1 Colleges, preferred (Stability) : - Candidate must have spent minimum 3 yrs in each (Experience) : - Must have recent 4+ YOE with high-growth Product startups, and should have implemented Data Engineering systems from an early stage in the Companies :Hevo Data, Mixpanel, Segment, Zarget, MoEngage, WebEngage, CleverTap, Netcore Cloud, Lemnisk, Vizury, RudderStack, Actyv.ai etcJob Specific Criteria :CV Attachment is mandatoryDo you have team leading experience? How many members have you handled in a team?.Have you setup data engineering for a company from scratch (0 to 1. end to end)? Please share details?What is the largest data size you have worked on and in which company? Please share detail?This role requires hands-on coding - are you comfortable with this?Please provide Current CTC Breakup (Fixed & Variable)What's your current company ?As a Lead Data Engineering, you will play a pivotal role in defining the organizations data vision, architecture, and technical direction. This role blends hands-on technical expertise with strategic leadership guiding teams, optimizing infrastructure, and driving innovation. Youll be responsible for building and scaling robust, high-performance data systems that empower business intelligence, analytics, and product decisions across the & Responsibilities :Lead and Mentor the Data Engineering Team- Build, manage, and inspire a high-performing team of data engineers. Provide mentorship, conduct regular performance reviews, and design personalized growth paths for each team member. Encourage continuous learning, technical excellence, and collaboration across teams.Architect and Optimize Scalable Data Infrastructure- Design and maintain large-scale, fault-tolerant, and high-availability data infrastructure. Youll ensure end-to-end data flow from ingestion and transformation to analytics and storage runs smoothly, efficiently, and securely across platforms.Drive Data Governance and Best Practices- Develop and implement data governance frameworks that prioritize data quality, consistency, and security. Establish standards for data lineage, metadata management, and documentation to ensure reliability and transparency across all Cross-Functionally to Define a Data Roadmap- Partner with Product Managers, Data Scientists, and Business Analysts to translate company goals into actionable data strategies. Align data initiatives with product objectives and help shape data-driven decision-making across business units.Optimize Data Processing Workflows- Lead efforts to enhance data ingestion, ETL, and analytics workflows. Identify and resolve performance bottlenecks, reduce data latency, and streamline pipelines using distributed computing and Data Security, Compliance, and Quality- Build security-focused systems that adhere to compliance standards like GDPR and SOC2. Implement access control, encryption, and monitoring tools to ensure data integrity and confidentiality across all systems.Foster a Culture of Innovation and Technical Excellence- Encourage experimentation and adoption of cutting-edge technologies. Set high coding and architectural standards, lead design reviews, and promote a culture of excellence that values creativity and Candidate :The ideal candidate is a seasoned engineering leader with a passion for scalable systems, deep technical expertise, and a proven record of leading data-driven & Leadership :- 10+ years of experience in software or data engineering, with at least 3 years in a leadership or managerial capacity.- Strong experience leading high-impact data projects and cross-functional technical Expertise :- Strong backend development experience using Java, PHP, Python, Node.js, GoLang, JavaScript, HTML, and CSS.- Advanced proficiency in SQL, Python, and Scala for data analytics, pipeline design, and processing.- Expertise in cloud platforms (AWS, GCP, or Azure) and familiarity with their respective data services (e.g., Redshift, Snowflake, BigQuery).- Strong understanding of HLD (High-Level Design) and LLD (Low-Level Design) principles, along with design patterns using Spring Boot or Google Guice.- Hands-on experience with Big Data technologies Spark, Hadoop, Kafka, and distributed processing frameworks.- Deep understanding of data warehousing solutions, including Snowflake, Redshift, and BigQuery.- Working experience with NoSQL databases such as Redis, Cassandra, MongoDB, and and Automation Knowledge :- Experience with CI/CD pipelines and modern automation tools such as Jenkins, Ansible, Docker, Kubernetes, Chef, Grafana, and ELK.- Strong ability to automate infrastructure and ensure system reliability with minimal manual Security, and Compliance :- Deep knowledge of data governance, privacy regulations, and compliance frameworks such as GDPR and SOC 2.- Proven experience establishing scalable data security protocols and and Analytical Thinking :- Capable of aligning technical strategy with long-term business objectives.- Strong communication and stakeholder management skills able to translate technical concepts into actionable business Qualifications Learning Infrastructure / MLOps :- Experience designing or managing systems for model deployment, monitoring, and Data Processing :- Exposure to event-driven architectures and tools like Kafka Streams, Flink, or and Architectural Interest :- Deep interest in data structures, algorithm optimization, distributed computing, and high-performance architecture Background :- Prior experience in SaaS, product-based, or high-growth technology environments is a Benefits & Work Culture :Youll be part of an environment that encourages autonomy, creativity, and innovation. The team believes in breaking conventions, building frameworks from scratch, and questioning traditional boundaries. Every engineer is empowered to think independently, experiment boldly, and contribute meaningfully to both product and technical direction. (ref:hirist.tech)