SQL Developer

Role and Responsibilities

• Own the product analytics of bidgely’s end user-facing products, measure and identify areas of improvement through data
• Liaise with Product Managers and Business Leaders to understand the product issues, priorities and hence support them through relevant product analytics
• Own the automation of product analytics through good SQL knowledge
• Develop early warning metrics for production and highlight issues and breakdowns for resolution
• Resolve client escalations and concerns regarding key business metrics
• Define and own execution
• Own the Energy Efficiency program designs, dashboard development, and monitoring of existing Energy efficiency program
• Deliver data-backed analysis and statistically proven solutions
• Research and implement best practices
• Mentor team of analysts

Qualifications and Education Requirements

• B.Tech from a premier institute with 5+ years analytics experience or Full-time MBA from a premier b-school with 3+ years of experience in analytics/business or product analytics
• Bachelor's degree in Business, Computer Science, Computer Information Systems, Engineering, Mathematics, or other business/analytical disciplines

Skills needed to excel

• Proven analytical and quantitative skills and an ability to use data and metrics to back up assumptions, develop business cases, and complete root cause
  analyses
• Excellent understanding of retention, churn, and acquisition of user base
• Ability to employ statistics and anomaly detection techniques for data-driven
  analytics
• Ability to put yourself in the shoes of the end customer and understand what
  “product excellence” means
• Ability to rethink existing products and use analytics to identify new features and product improvements.
• Ability to rethink existing processes and design new processes for more effective analyses
• Strong SQL knowledge, working experience with Looker and Tableau a great plus
• Strong commitment to quality visible in the thoroughness of analysis and techniques employed
• Strong project management and leadership skills
• Excellent communication (oral and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams
• Ability to coach and mentor analysts on technical and analytical skills
• Good knowledge of statistics, basic machine learning, and AB Testing is
  preferable
• Experience as a Growth hacker and/or in Product analytics is a big plus

1. 2 to 4 years of experience
2. hands on experience using python, sql, tablaue
3. Data Analyst 

Tech Skills:
• Hadoop Ecosystem (HBase, Hive, MapReduce, HDFS, Pig, Sqoop etc)
• should have good hands-on Spark (spark with java/PySpark)
• Hive
• must be good with SQL's(spark SQL/ HiveQL)
• Application design, software development and automated testing
Environment Experience:
• Experience with implementing integrated automated release management using tools/technologies/frameworks like Maven, Git, code/security review tools, Jenkins, Automated testing, and Junit.
• Demonstrated experience with Agile or other rapid application development methods
• Cloud development (AWS/Azure/GCP)
• Unix / Shell scripting
• Web services , open API development, and REST concepts

THE IDEAL CANDIDATE WILL

 

• Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
• Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
• Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
• Work hands-on across various MLOps problems and provide thought leadership
• Grow and manage large teams with diverse skillsets
• Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists

 

 

 

ELIGIBILITY CRITERIA

 

• BE/BTech/MTech (Specialization/courses in ML/DS)
• At-least 7+ years of Consulting services delivery experience
• Very strong problem-solving skills & work ethics
• Possesses strong analytical/logical thinking, storyboarding and executive communication skills
• 5+ years of experience in Python/R, SQL
• 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
• Hands on work experience in DevOps
• Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
• Exposure on cloud technologies like Azure, AWS or GCP
• Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
• Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
• Experience with one or more Container-ecosystem (Docker, Kubernetes)
• Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
• Good understanding of OOP & Data Structures concepts

 

 

Nice to Have:

 

• Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
• Experience in Helm is a plus
• Strong understanding of data infrastructure, data warehouse, or data engineering

 

You can expect to –

• Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
• Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
• Work in a diverse environment that keeps evolving
• Hone your entrepreneurial skills as you contribute to growth of the organization

 

 

Company Profile
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.

• Responsible for developing and maintaining applications with PySpark 

• 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.

• 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.