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XpressBees – a logistics company started in 2015 – is amongst the fastest growing
companies of its sector. While we started off rather humbly in the space of
ecommerce B2C logistics, the last 5 years have seen us steadily progress towards
expanding our presence. Our vision to evolve into a strong full-service logistics
organization reflects itself in our new lines of business like 3PL, B2B Xpress and cross
border operations. Our strong domain expertise and constant focus on meaningful
innovation have helped us rapidly evolve as the most trusted logistics partner of
India. We have progressively carved our way towards best-in-class technology
platforms, an extensive 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 improve efficiencies for our clients.
Job Profile
As a Lead Data Engineer in the Data Platform Team at XpressBees, you will build the data platform
and infrastructure to support high quality and agile decision-making in our supply chain and logistics
workflows.
You will define the way we collect and operationalize data (structured / unstructured), and
build production pipelines for our machine learning models, and (RT, NRT, Batch) reporting &
dashboarding requirements. As a Senior Data Engineer in the XB Data Platform Team, you will use
your experience with modern cloud and data frameworks to build products (with storage and serving
systems)
that drive optimisation and resilience in the supply chain via data visibility, intelligent decision making,
insights, anomaly detection and prediction.
What You Will Do
• Design and develop data platform and data pipelines for reporting, dashboarding and
machine learning models. These pipelines would productionize machine learning models
and integrate with agent review tools.
• Meet the data completeness, correction and freshness requirements.
• Evaluate and identify the data store and data streaming technology choices.
• Lead the design of the logical model and implement the physical model to support
business needs. Come up with logical and physical database design across platforms (MPP,
MR, Hive/PIG) which are optimal physical designs for different use cases (structured/semi
structured). Envision & implement the optimal data modelling, physical design,
performance optimization technique/approach required for the problem.
• Support your colleagues by reviewing code and designs.
• Diagnose and solve issues in our existing data pipelines and envision and build their
successors.
Qualifications & Experience relevant for the role
• A bachelor's degree in Computer Science or related field with 6 to 9 years of technology
experience.
• Knowledge of Relational and NoSQL data stores, stream processing and micro-batching to
make technology & design choices.
• Strong experience in System Integration, Application Development, ETL, Data-Platform
projects. Talented across technologies used in the enterprise space.
• Software development experience using:
• Expertise in relational and dimensional modelling
• Exposure across all the SDLC process
• Experience in cloud architecture (AWS)
• Proven track record in keeping existing technical skills and developing new ones, so that
you can make strong contributions to deep architecture discussions around systems and
applications in the cloud ( AWS).
• Characteristics of a forward thinker and self-starter that flourishes with new challenges
and adapts quickly to learning new knowledge
• Ability to work with a cross functional teams of consulting professionals across multiple
projects.
• Knack for helping an organization to understand application architectures and integration
approaches, to architect advanced cloud-based solutions, and to help launch the build-out
of those systems
• Passion for educating, training, designing, and building end-to-end systems.
Job Description for :
Role: Data/Integration Architect
Experience – 8-10 Years
Notice Period: Under 30 days
Key Responsibilities: Designing, Developing frameworks for batch and real time jobs on Talend. Leading migration of these jobs from Mulesoft to Talend, maintaining best practices for the team, conducting code reviews and demos.
Core Skillsets:
Talend Data Fabric - Application, API Integration, Data Integration. Knowledge on Talend Management Cloud, deployment and scheduling of jobs using TMC or Autosys.
Programming Languages - Python/Java
Databases: SQL Server, Other Databases, Hadoop
Should have worked on Agile
Sound communication skills
Should be open to learning new technologies based on business needs on the job
Additional Skills:
Awareness of other data/integration platforms like Mulesoft, Camel
Awareness Hadoop, Snowflake, S3
A global business process management company
Designation – Deputy Manager - TS
Job Description
- Total of 8/9 years of development experience Data Engineering . B1/BII role
- Minimum of 4/5 years in AWS Data Integrations and should be very good on Data modelling skills.
- Should be very proficient in end to end AWS Data solution design, that not only includes strong data ingestion, integrations (both Data @ rest and Data in Motion) skills but also complete DevOps knowledge.
- Should have experience in delivering at least 4 Data Warehouse or Data Lake Solutions on AWS.
- Should be very strong experience on Glue, Lambda, Data Pipeline, Step functions, RDS, CloudFormation etc.
- Strong Python skill .
- Should be an expert in Cloud design principles, Performance tuning and cost modelling. AWS certifications will have an added advantage
- Should be a team player with Excellent communication and should be able to manage his work independently with minimal or no supervision.
- Life Science & Healthcare domain background will be a plus
Qualifications
BE/Btect/ME/MTech
Responsibilities for Data Engineer
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
Qualifications for Data Engineer
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Develop complex queries, pipelines and software programs to solve analytics and data mining problems
Interact with other data scientists, product managers, and engineers to understand business problems, technical requirements to deliver predictive and smart data solutions
Prototype new applications or data systems
Lead data investigations to troubleshoot data issues that arise along the data pipelines
Collaborate with different product owners to incorporate data science solutions
Maintain and improve data science platform
Must Have
BS/MS/PhD in Computer Science, Electrical Engineering or related disciplines
Strong fundamentals: data structures, algorithms, database
5+ years of software industry experience with 2+ years in analytics, data mining, and/or data warehouse
Fluency with Python
Experience developing web services using REST approaches.
Proficiency with SQL/Unix/Shell
Experience in DevOps (CI/CD, Docker, Kubernetes)
Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication skills, ability to multi-task and manage expectations
Preferred
Industry experience with big data processing technologies such as Spark and Kafka
Experience with machine learning algorithms and/or R a plus
Experience in Java/Scala a plus
Experience with any MPP analytics engines like Vertica
Experience with data integration tools like Pentaho/SAP Analytics Cloud