Amit Dass

Operations Associate

London, England, United Kingdom14 yrs 4 mos experience
AI ML PractitionerAI Enabled

Key Highlights

  • 14+ years of experience in Data Engineering.
  • Led critical development work and optimized big data jobs.
  • Received multiple awards for exceptional contributions.
Stackforce AI infers this person is a Data Engineering and AI Solutions Architect with expertise in Cloud technologies.

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Skills

Core Skills

Data EngineeringData SolutionsBig Data

Other Skills

AI technologiesData workflowsDatabricksTraining and enablementData architecturesData ModelingCloud ComputingScalaSparkHadoopKafkaApache KafkaApache FlumeApache SqoopMapReduce

About

Amit is a Digital Data Engineering Manager (Lead Data Engineer & Architect) & Microsoft Certified Trainer (MCT) Total IT experience of 14+ years. Expertise in Data Engineering with Cloud (AWS, Azure, and GCP) / Databricks & Cloudera (CDP public cloud) Exposure of Kubernetes (K8s) on Azure Cloud(AKS) and make Kstream applications scalable. Exposure of Machine Learning Models and relevant services in the Cloud. Worked with Clients - UK Banks, UK Insurance, Aerospace & Defence, US & UK Telecom My Top Strengths are : 1. Data Engineering Design and implementation using any programming language Like Python, Scala or Java. 2. Data Solutions, Architecture design, and implementation. 3. Data Governance and GDPR implementation. 4. Always open to new challenges and learning. Role and Responsibility : • Regular discussion with clients and stakeholders on design architecture & solutions. • Translate complex functional and technical requirements into detailed design. • Responsibility to come up with the best design solution and leading the critical development work. • Leading daily scrum calls with team and stakeholders on current progress and upcoming plans. • Support team on their development work if they find anything difficult (Experienced in optimizing big data jobs related to Memory, Data Skew, and small files & performance tuning for Spark-SQL as well as Spark code). . Fine-tune Spark & Kafka applications for high performance and throughput. • Developed reusable components/plug-ins which will be enhanced and leveraged across ingestion pipeline. I have also developed a framework where we anonymize(mask) the production data and use it in testing, this helps us to face real production challenges. • Schedule demo for the client, when the sprint completes. This is to show our development progress from time to time. • Report Senior Manager and Managing Director about the status of the project in a weekly manner. • Production deployment of the end product after all testing phases successfully completed. Recognization: Received 8 awards in the years 2021-2022 for my exceptional contribution towards Project and DTE activities. Received 5 awards in the year 2022 -2023 including Most Inspirational Leader Award and Client Value Creation Award.

Experience

14 yrs 4 mos
Total Experience
4 yrs
Average Tenure
2 yrs 3 mos
Current Experience

Kpmg uk

Data Engineering Manager

Jan 2024Present · 2 yrs 3 mos · London Area, United Kingdom · Hybrid

  • As a Data Solutions Manager, I drive innovative data strategies, ensuring seamless integration of AI technologies and optimizing data workflows.
Data EngineeringAI technologiesData workflowsData Solutions

Accenture uk & ireland

2 roles

Global Enablement Lead and Data Engineering Manager

Promoted

Dec 2023Jan 2024 · 1 mo

  • As the Global Enablement Lead for Databricks, I orchestrate and deliver world-class training and enablement programs. I empower teams across the globe with the skills and knowledge needed to maximize the capabilities of the Databricks platform. Collaborating with cross-functional stakeholders, I ensure that organizations extract actionable insights and drive innovation through cutting-edge data and AI technologies.
  • As a Data Engineering Manager, I lead a high-performing team dedicated to designing and implementing robust data architectures. From conceptualization to execution, my team and I are at the forefront of architecting scalable and efficient data pipelines. Leveraging a combination of technical expertise and strategic vision, we optimize data workflows to fuel advanced analytics, machine learning, and business intelligence initiatives.
DatabricksTraining and enablementData architecturesData EngineeringData Solutions

Team Lead Manager

Aug 2018Jan 2024 · 5 yrs 5 mos

Data ModelingCloud Computing

Capgemini

Big Data Sr Consultant

May 2017Aug 2018 · 1 yr 3 mos

  • Language : Scala 2.10
  • Framework : Spark 1.6 Hadoop distribution : HDP 2.5
  • Ecosystem tool : Kafka for streaming Database : Phoenix (Hbase)
  • Domain : Telecom with US client
  • Roles and responsibility :
  • Understanding requirement with client and design architecture
  • Preparing LLD with reference to HLD and SRS.
  • Handling team as well as developing the Spark Streaming application.
  • Following GIT process creating ansible scripts , pull request for review and code push to respective branch.
  • Deploying spark application using Jenkins on Dev,QA and PROD.
  • Reviewing GIT code , Jenkins build and Sonarqube reports.
  • Using Teamforge tool to raise defects and assign to developer .
ScalaSparkHadoopKafkaBig DataData Engineering

Tata consultancy services

IT Analyst

Dec 2011May 2017 · 5 yrs 5 mos

  • To Analyse the data which is semi structure or structure coming from different sources like sensor, servers or RDBMS data using Apache Kafka ,Apache Flume and Apache Sqoop then put the data into hdfs/hive/hbase then analyze the data using Mapreduce /Apache Spark -Core and Spark-Sql and then store into Hive table /HBASE which can be viewed in SAP IDT/TIBCO Jaspersoft ( by selecting data source as hive table) and display the report and graph as per the requirement.
Apache KafkaApache FlumeApache SqoopMapReduceApache SparkData Engineering+1

Education

G.H.Raisoni College Of Engg

B.E.(IT) — SCIENCE

Jan 2007Jan 2011

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