4B_Sr. Technical Lead_Databricks Job Vacancy in Incedo Gurgaon, Haryana – Updated today

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Company Name : Incedo
Location : Gurgaon, Haryana
Position :

Job Description : Company Overview Company Overview

Incedo is a US-based consulting, data science and technology services firm with over 2,500 people helping clients from our six offices across US and India. We help our clients achieve competitive advantage through end-to-end digital transformation. Our uniqueness lies in bringing together strong engineering, data science, and design capabilities coupled with deep domain understanding. We combine services and products to maximize business impact for our clients in telecom, financial services, product engineering and life science & healthcare industries.
Working at Incedo will provide you an opportunity to work with industry leading client organizations, deep technology and domain experts, and global teams. Incedo University, our learning platform, provides ample learning opportunities starting with a structured onboarding program and carrying throughout various stages of your career. A variety of fun activities are also an integral part of our friendly work environment. Our flexible career paths allow you to grow into a program manager, a technical architect or a domain expert based on your skills and interests.
4B_Sr.Technical Lead

Role and responsibilities

Creating Project Technical Documentation
Designing Solution architecture, and work on Data Ingestion, Preparation and Transformation.
Debugging the production failures and identifying the solution.
Developing efficient cloud data processing frameworks using Databricks and PySpark on AWS platform.
Enabling Data Governance and Data Discovery on AWS Platform
Building data processing framework using Talend, Databricks Spark,Spark SQL
Exposure of Data Pipeline Automation using DevOps tools
Exposure of Job Monitoring framework along validations automation
Exposure of handling structured, Unstructured and Streaming data.

Technical skills requirements

The candidate must demonstrate proficiency in,
Solid hands-on working experience in Big-Data Technologies
Strong hands-on experience of programming language with Python or Scala with Databricks Spark.
Good command and working experience on Hadoop/Map Reduce, HDFS, Hive, HBase, and No-SQL Databases
Hands on working experience on any of the data engineering/analytics platform on AWS
Hands on working experience of data processing at scale with event driven systems, message queues (Kafka/ Flink/Spark Streaming)
Hands on working Experience with AWS Services like EMR, Kinesis, S3, Cloud formation, Glue, API Gateway, Lake Foundation
Hands on working Experience with AWS Athena
Operationalization of ML models on AWS (e.g. deployment, scheduling, model monitoring etc.)
Experience gathering and processing raw data at scale (including writing scripts, web scraping, calling APIs, write SQL queries, etc.)
Experience building data pipelines for structured/unstructured, real-time/batch, events/synchronous/ asynchronous using MQ, Kafka, Steam processing
Hands-on working experience in analyzing source system data and data flows, working with structured and unstructured data
Must be very strong in writing Spark SQL queries
Strengthen the Data engineering team with Big Data solutions
Strong technical, analytical, and problem-solving skills
Strong organizational skills, with the ability to work autonomously as well as in a team-based environment
Pleasant Personality, Strong Communication & Interpersonal Skills

Nice-to-have skills

Scripting: Unix or Shell scripting
Strong preference for someone with Amazon Web Services (AWS) Databricks Spark expertise
Exposure to various ETL and Business Intelligence tools

Qualifications

A bachelor’s degree in computer science, computer engineering, or a related discipline is required to work as a technical lead
Bigdata Certification on AWS and Databricks Spark would be a big plus

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Company Value Company Value

We are an Equal Opportunity Employer. We value diversity at Incedo. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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