Responsibilities:
- Creating a positive onboarding experience for new clients.
- Manage daily activities and tasks for clients by Line Manager
- Regularly interacting with clients through telephone calls, email communications, or face-to-face meetings.
- Responding to clients' requests as they arise in real time
- Maintaining an accurate record of all necessary documents pertaining to the brand.
- Coordinate with various internal teams to deliver Creative, Data Analytics, Tech and Operational Services
- Develop a relationship with clients and manage their expectations (Kudos if you can balance the two together!)
- Upsell! Always be on the lookout to identify opportunities and convert them to grow revenue
- Ensure that projects are completed on time and within budget.
- Coach and support team members to help them meet departmental goals
- Take responsibility for the quality of work, the accuracy of the brief, and the team’s output
- Maintain weekly, fortnightly, and monthly reports
- Meeting clients to discuss strategy and report on progress
- Keep ahead of the industry’s developments and apply best practices to areas of improvement
- Maintain an orderly workflow according to priorities
BECOME A PEOPLE’S PERSON!
- Exhibit strong leadership skills and inspire your team members
- Stick to the client’s brief and the agreed process to deliver effectively
- Utilize your team’s productivity keeping the Scope Of Work and allocated budget
- Be all ears to Account Managers and mentors to get the best performance possible
IMPROVE THE PROCESS!
- Relentlessly work on improving the internal processes while solving problems along the way
COMMUNICATE AND COLLABORATE!
- Manage all business communications
- Become a link for the internal team and make sure the process is consistently followed until the project is completed as per the client’s brief
SKILLS WE DESIRE
- Develop and maintain existing client relationships.
- Excellent organizational and time management skills.
- Strong analytical and problem-solving skills.
- Effective communication skills.
- A+ presentation skills (making PPTs included)
- Natural attention to detail
- Financial management and commercial acumen
- Advanced software skills including Word

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Job Description: Data Engineer
Location: Remote
Experience Required: 6 to 12 years in Data Engineering
Employment Type: [Full-time]
Notice: Looking for candidates, Who can join immediately or 15days Max
About the Role:
We are looking for a highly skilled Data Engineer with extensive experience in Python, Databricks, and Azure services. The ideal candidate will have a strong background in building and optimizing ETL processes, managing large-scale data infrastructures, and implementing data transformation and modeling tasks.
Key Responsibilities:
ETL Development:
Use Python as an ETL tool to read data from various sources, perform data type transformations, handle errors, implement logging mechanisms, and load data into Databricks-managed delta tables.
Develop robust data pipelines to support analytics and reporting needs.
Data Transformation & Optimization:
Perform data transformations and evaluations within Databricks.
Work on optimizing data workflows for performance and scalability.
Azure Expertise:
Implement and manage Azure services, including Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
Coding & Development:
Utilize Python for complex tasks involving classes, objects, methods, dictionaries, loops, packages, wheel files, and database connectivity.
Write scalable and maintainable code to manage streaming and batch data processing.
Cloud & Infrastructure Management:
Leverage Spark, Scala, and cloud-based solutions to design and maintain large-scale data infrastructures.
Work with cloud data warehouses, data lakes, and storage formats.
Project Leadership:
Lead data engineering projects and collaborate with cross-functional teams to deliver solutions on time.
Required Skills & Qualifications:
Technical Proficiency:
- Expertise in Python for ETL and data pipeline development.
- Strong experience with Databricks and Apache Spark.
- Proven skills in handling Azure services, including Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
Experience & Knowledge:
- Minimum 6+ years of experience in data engineering.
- Solid understanding of data modeling, ETL processes, and optimizing data pipelines.
- Familiarity with Unix shell scripting and scheduling tools.
Other Skills:
- Knowledge of cloud warehouses and storage formats.
- Experience in handling large-scale data infrastructures and streaming data.
Preferred Qualifications:
- Proven experience with Spark and Scala for big data processing.
- Prior experience in leading or mentoring data engineering teams.
- Hands-on experience with end-to-end project lifecycle in data engineering.
What We Offer:
- Opportunity to work on challenging and impactful data projects.
- A collaborative and innovative work environment.
- Competitive compensation and benefits.
How to Apply:
Requirements:
6+ year of working experience .
Strong understanding of web fundamentals
Deeply technical with a track record of successful delivery.
Manage daily/weekly scrums.
Lead technical strategy and implementation for various team initiatives with an alignment with project / client expectations
Proven record of building project from scratch.
An entrepreneurial spirit combined with strong program and project management skills.
Excellent written and verbal communication skills with the ability to present complex plans and designs.
Excellent judgment, organizational, and problem-solving skills.
Excellent design and architecture knowledge.
Data-driven decision making.
What is expected from you :
● Strong Consultative selling skills including excellent relationship building, networking
and time management skills
● Excellent Conflict Resolution and Negotiation skills
● Strong Team Player
● Excellent in Business communications and email etiquette
● Exposure to LinkedIn and other Job portals
● Ability to generate B2B leads
● Experience in Lead Research and Prospecting
● Experience in cold calling, email campaigns, and using social media to generate leads.
● Knowledge of Recruitment
● Data Maintenance and organization skills
● MBA qualification or Experience in Business development is preferred
What will you be doing?
● Handle end-to-end B2B business Development, right from prospecting to closing
deals
● Acquire new clients through networking, direct contact, or from marketing campaigns
● Establish long-term engagement with clients with multiple products
● Build and nurture client relationships via various channels
● Coordinating with multiple internal stakeholders on a daily basis
● Cross-selling and Upselling to existing clients into other GUVI services
● Develop and implement marketing plans designed to maintain and increase existing
business and capture new opportunities
- Oracle HCM Techno-Functional Consultant, core HR, Payroll, Fast Formula, OTL and SSHR, Oracle HCM Cloud advanced tools (HCM Extracts, HDL, PBL,
BI Publisher, OTBI, Application Security, Page Composer, Page Configurator, REST APIs, SOAP, Webservices)


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.
Key Result Areas –
- Deliver projects/ Products with a world-class user interface and experience
- Delivering as per the plan following the deadline, quality & process.
- Adhering to the company productivity & quality matrix
- Keep the focus on automation and reuse of the component
- Project documentation
- Effective communication
- Following the company defined coding standards
- Contribution to common code
- Should be able to work in agile development methodology.
Skills Required-
- Strong Experience in ExpressJS, Node.JS, HTML, CSS, JavaScript
- Experience in Angular 1 / 4 / 5 will be a big plus
- Comfortable with source code repositories Git
- Worked with build tools like Gulp, Bower, npm
- Experience in developing REST APIs using Node.js
- Strong Experience in MongoDB
- Should be able to understand existing code and able to enhance it further as required.
- Knowledge of agile development methodology.

• Build application logic & develop user-facing features in Kotlin and Java.
• Translate designs & wireframes into high-quality code.
• Build reusable components & front-end libraries for future use, as and wherever needed.
• Define front-end architecture, document, estimate scope, & deliver on time.
Candidate profile:
• At least 2 years of professional experience building native projects for Android.
• Have at least one live project.
• Practical knowledge of working with RESTful APIs, & version control tools such as git.
• Experience creating custom libraries.
• Proficiency in various software design patterns.
• Accountable & proactive communicator.
• Has worked in an agile or iterative environment. Can estimate scope & prioritize.
• Independent problem solver. Comfortable with ambiguity & fast pace start-up work culture.
Bonus points:
• If you have previous experience in node js and react
• If you have previous experience in building webrtc products





