Senior Data Engineer

Job Responsibilities:

• Project Planning and Management
o Take end-to-end ownership of multiple projects / project tracks
o Create and maintain project plans and other related documentation for project
objectives, scope, schedule and delivery milestones
o Lead and participate across all the phases of software engineering, right from
requirements gathering to GO LIVE
o Lead internal team meetings on solution architecture, effort estimation, manpower
planning and resource (software/hardware/licensing) planning
o Manage RIDA (Risks, Impediments, Dependencies, Assumptions) for projects by
developing effective mitigation plans
• Team Management
o Act as the Scrum Master
o Conduct SCRUM ceremonies like Sprint Planning, Daily Standup, Sprint Retrospective
o Set clear objectives for the project and roles/responsibilities for each team member
o Train and mentor the team on their job responsibilities and SCRUM principles
o Make the team accountable for their tasks and help the team in achieving them
o Identify the requirements and come up with a plan for Skill Development for all team
members
• Communication
o Be the Single Point of Contact for the client in terms of day-to-day communication
o Periodically communicate project status to all the stakeholders (internal/external)
• Process Management and Improvement
o Create and document processes across all disciplines of software engineering
o Identify gaps and continuously improve processes within the team
o Encourage team members to contribute towards process improvement
o Develop a culture of quality and efficiency within the team

Must have:
• Minimum 08 years of experience (hands-on as well as leadership) in software / data engineering
across multiple job functions like Business Analysis, Development, Solutioning, QA, DevOps and
Project Management
• Hands-on as well as leadership experience in Big Data Engineering projects
• Experience developing or managing cloud solutions using Azure or other cloud provider
• Demonstrable knowledge on Hadoop, Hive, Spark, NoSQL DBs, SQL, Data Warehousing, ETL/ELT,
DevOps tools
• Strong project management and communication skills
• Strong analytical and problem-solving skills
• Strong systems level critical thinking skills
• Strong collaboration and influencing skills

Good to have:
• Knowledge on PySpark, Azure Data Factory, Azure Data Lake Storage, Synapse Dedicated SQL
Pool, Databricks, PowerBI, Machine Learning, Cloud Infrastructure
• Background in BFSI with focus on core banking
• Willingness to travel

Work Environment
• Customer Office (Mumbai) / Remote Work

Education
• UG: B. Tech - Computers / B. E. – Computers / BCA / B.Sc. Computer Science

Company Profile
XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
vision to evolve into a strong full-service logistics organization reflects itself in the various lines of business like B2C
logistics 3PL, B2B Xpress, Hyperlocal and Cross border Logistics.
Our strong domain expertise and constant focus on innovation has helped us rapidly evolve as the most trusted
logistics partner of India. XB has progressively carved our way towards best-in-class technology platforms, an
extensive logistics network reach, and a seamless last mile management system.
While on this aggressive growth path, we seek to become the one-stop-shop for end-to-end logistics solutions. Our
big focus areas for the very near future include strengthening our presence as service providers of choice and
leveraging the power of technology to drive supply chain efficiencies.
Job Overview
XpressBees would enrich and scale its end-to-end logistics solutions at a high pace. This is a great opportunity to join
the team working on forming and delivering the operational strategy behind Artificial Intelligence / Machine Learning
and Data Engineering, leading projects and teams of AI Engineers collaborating with Data Scientists. In your role, you
will build high performance AI/ML solutions using groundbreaking AI/ML and BigData technologies. You will need to
understand business requirements and convert them to a solvable data science problem statement. You will be
involved in end to end AI/ML projects, starting from smaller scale POCs all the way to full scale ML pipelines in
production.
Seasoned AI/ML Engineers would own the implementation and productionzation of cutting-edge AI driven algorithmic
components for search, recommendation and insights to improve the efficiencies of the logistics supply chain and
serve the customer better.
You will apply innovative ML tools and concepts to deliver value to our teams and customers and make an impact to
the organization while solving challenging problems in the areas of AI, ML , Data Analytics and Computer Science.
Opportunities for application:
- Route Optimization
- Address / Geo-Coding Engine
- Anomaly detection, Computer Vision (e.g. loading / unloading)
- Fraud Detection (fake delivery attempts)
- Promise Recommendation Engine etc.
- Customer & Tech support solutions, e.g. chat bots.
- Breach detection / prediction
An Artificial Intelligence Engineer would apply himself/herself in the areas of -
- Deep Learning, NLP, Reinforcement Learning
- Machine Learning - Logistic Regression, Decision Trees, Random Forests, XGBoost, etc..
- Driving Optimization via LPs, MILPs, Stochastic Programs, and MDPs
- Operations Research, Supply Chain Optimization, and Data Analytics/Visualization
- Computer Vision and OCR technologies
The AI Engineering team enables internal teams to add AI capabilities to their Apps and Workflows easily via APIs
without needing to build AI expertise in each team – Decision Support, NLP, Computer Vision, for Public Clouds and
Enterprise in NLU, Vision and Conversational AI.Candidate is adept at working with large data sets to find
opportunities for product and process optimization and using models to test the effectiveness of different courses of
action. They must have knowledge using a variety of data mining/data analysis methods, using a variety of data tools,
building, and implementing models, using/creating algorithms, and creating/running simulations. They must be
comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Roles & Responsibilities
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection,
Risk prevention, Predictive analytics), computer vision, natural language processing (NLP) and speech that
work out of the box.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Build core of Artificial Intelligence and AI Services such as Decision Support, Vision, Speech, Text, NLP, NLU,
and others.
● Leverage Cloud technology –AWS, GCP, Azure
● Experiment with ML models in Python using machine learning libraries (Pytorch, Tensorflow), Big Data,
Hadoop, HBase, Spark, etc
● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to
drive business solutions.
● Mine and analyze data from company databases to drive optimization and improvement of product
development, marketing techniques and business strategies.
● Assess the effectiveness and accuracy of new data sources and data gathering techniques.
● Develop custom data models and algorithms to apply to data sets.
● Use predictive modeling to increase and optimize customer experiences, supply chain metric and other
business outcomes.
● Develop company A/B testing framework and test model quality.
● Coordinate with different functional teams to implement models and monitor outcomes.
● Develop processes and tools to monitor and analyze model performance and data accuracy.
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Deliver machine learning and data science projects with data science techniques and associated libraries
such as AI/ ML or equivalent NLP (Natural Language Processing) packages. Such techniques include a good
to phenomenal understanding of statistical models, probabilistic algorithms, classification, clustering, deep
learning or related approaches as it applies to financial applications.
● The role will encourage you to learn a wide array of capabilities, toolsets and architectural patterns for
successful delivery.
What is required of you?
You will get an opportunity to build and operate a suite of massive scale, integrated data/ML platforms in a broadly
distributed, multi-tenant cloud environment.
● B.S., M.S., or Ph.D. in Computer Science, Computer Engineering
● Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.
● Experience with building high-performance, resilient, scalable, and well-engineered systems
● Experience in CI/CD and development best practices, instrumentation, logging systems
● Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights
from large data sets.
● Experience working with and creating data architectures.
● Good understanding of various machine learning and natural language processing technologies, such as
classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.

● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest,
Boosting, Trees, text mining, social network analysis, etc.
● Knowledge on using web services: Redshift, S3, Spark, Digital Ocean, etc.
● Knowledge on creating and using advanced machine learning algorithms and statistics: regression,
simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
● Knowledge on analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics,
AdWords, Crimson Hexagon, Facebook Insights, etc.
● Knowledge on distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, Kafka etc.
● Knowledge on visualizing/presenting data for stakeholders using: Quicksight, Periscope, Business Objects,
D3, ggplot, Tableau etc.
● Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
● Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests, and proper usage, etc.) and experience with applications.
● Experience building data pipelines that prep data for Machine learning and complete feedback loops.
● Knowledge of Machine Learning lifecycle and experience working with data scientists
● Experience with Relational databases and NoSQL databases
● Experience with workflow scheduling / orchestration such as Airflow or Oozie
● Working knowledge of current techniques and approaches in machine learning and statistical or
mathematical models
● Strong Data Engineering & ETL skills to build scalable data pipelines. Exposure to data streaming stack (e.g.
Kafka)
● Relevant experience in fine tuning and optimizing ML (especially Deep Learning) models to bring down
serving latency.
● Exposure to ML model productionzation stack (e.g. MLFlow, Docker)
● Excellent exploratory data analysis skills to slice & dice data at scale using SQL in Redshift/BigQuery.

Technology Skills (Good to Have):

We are looking for BE/BTech graduates (2018/2019 pass out) who want to build their career as Data Engineer covering technologies like Hadoop, NoSQL, RDBMS, Spark, Kafka, Hive, ETL, MDM & Data Quality. You should be willing to learn, explore, experiment, develop POCs/Solutions using these technologies with guidance and support from highly experienced Industry Leaders. You should be passionate about your work and willing to go extra mile to achieve results.

We are looking for candidates who believe in commitment and in building strong relationships. We need people who are passionate about solving problems through software and are flexible.

Required Experience, Skills and Qualifications

Passionate to learn and explore new technologies

Any RDBMS experience (SQL Server/Oracle/MySQL)

Any ETL tool experience (Informatica/Talend/Kettle/SSIS)

Understanding of Big Data technologies

Good Communication Skills

Excellent Mathematical / Logical / Reasoning Skills

Hi Candidates, Greetings From Publicvibe !!! We are Hiring NLP Engineers/ Data scientists in between 0.6 to 2.5 Years of Experience for our Hyderabad location, if anyone looking out for opportunities or Job change, reach out to us. Regards, Dhaneesha Dominic.

• Looking for Big Data Engineer with 3+ years of experience. • Hands-on experience with MapReduce-based platforms, like Pig, Spark, Shark. • Hands-on experience with data pipeline tools like Kafka, Storm, Spark Streaming. • Store and query data with Sqoop, Hive, MySQL, HBase, Cassandra, MongoDB, Drill, Phoenix, and Presto. • Hands-on experience in managing Big Data on a cluster with HDFS and MapReduce. • Handle streaming data in real time with Kafka, Flume, Spark Streaming, Flink, and Storm. • Experience with Azure cloud, Cognitive Services, Databricks is preferred.