3+ MapReduce Jobs in Delhi, NCR and Gurgaon | MapReduce Job openings in Delhi, NCR and Gurgaon

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.

Skills and competencies:

Required:

·        Strong analytical skills in conducting sophisticated statistical analysis using bureau/vendor data, customer performance

Data and macro-economic data to solve business problems.

·        Working experience in languages PySpark & Scala to develop code to validate and implement models and codes in

Credit Risk/Banking

·        Experience with distributed systems such as Hadoop/MapReduce, Spark, streaming data processing, cloud architecture.

• Familiarity with machine learning frameworks and libraries (like scikit-learn, SparkML, tensorflow, pytorch etc.
• Experience in systems integration, web services, batch processing
• Experience in migrating codes to PySpark/Scala is big Plus
• The ability to act as liaison conveying information needs of the business to IT and data constraints to the business

applies equal conveyance regarding business strategy and IT strategy, business processes and work flow

·        Flexibility in approach and thought process

·        Attitude to learn and comprehend the periodical changes in the regulatory requirement as per FED