Senior Data engineer

Your Day-to-Day

1. Derive Insights and drive major strategic projects to improve Business Metrics and take responsibility for cost efficiency and Revenue management across the country
2. Perform Market research, Post Mortem analyses on competitor expansion and Market Penetration patterns. 
3. Provide in-depth business analysis and data insights for internal stakeholders to help improve business. Derive and launch projects in order to reduce the gaps between targeted and projected business metrics
4. Responsible for optimizing Carsome’s C2B and B2C customer acquisition and Dealer retention funnel. Work closely with Marketing and Tech teams to create, produce and implement creative digital marketing campaigns and drive CRM initiatives and strategies 
5. Analyse the Revenue flows and processes large datasets to gather process insights and propose process improvement ideas for Carsome across SE-Asia
6. Lead commercial projects & process mapping, from conceptualization to completion, to build or re-engineer business models, tools and processes.
7. Having experience in analyses and insights in dealing on Unit Economics, COGs and P&L will be preferred ,but not mandatory
8. Use Business Intelligence and Data Science tools to answer the appropriate business problems using SQL, Tableau or Python.
9. Coordinate with HQ Data Insights Team and manage internal stakeholders across departments to ensure the smooth delivery of strategic projects
10. Work across different departments/functions (BI,DE, tech, pricing, finance, operations, marketing, CS,CX) and also on high impact projects and support business expansion initiatives

Your Know-Know

• At least a Bachelor's Degree in Accounting/Finance/Business or the equivalent. 
• 3-5  years of experience in strategy / consulting / analytical / project management roles; experience in e-commerce, Start-ups or Unicorns(CARS24,OLA,SWIGGY,FLIPKART,OYO) or entrepreneur experience preferred + At Least 2 years of experience leading a team
• Top-notch academics from a Tier 1 college (IIM / IIT/ NIT)
• Must have SQL/PostgreSQL/Tableau Experience. 
• Excellent Market Research, reporting and analytical skills, including carrying out weekly and monthly reporting
• Holds experience in working with Data/Business Intelligence Team
• Analytical mindset with ability to present data in a structured and informative way
• Enjoy a fast-paced environment and can align business objectives with product priorities
• Good to have : Financial modelling, Developing financial forecasts , development of Financial - strategic plan/framework

Looking for Big data Developers in Mumbai Location

DBMS & SQL
Concepts of RDBMS, Normalization techniques
Entity Relationship diagram/ ER-Model
Transaction, commit, rollback, ACID properties
Transaction log
Difference in behavior of the column if it is nullable
SQL Statements
Join Operations
DDL, DML, Data Modelling
Optimal Query writing - with Aggregate fn, Group By, having clause, Order by etc. Should be
hands on for scenario-based query Writing
Query optimizing technique, Indexing in depth
Understanding query plan
Batching
Locking schemes
Isolation levels
Concept of stored procedure, Cursor, trigger, View
Beginner level - PL/SQL - Procedure Function writing skill.
Spring JPA and Spring Data basics
Hibernate mappings

UNIX
Basic Concepts on Unix
Commonly used Unix Commands with their options
Combining Unix commands using Pipe Filter etc.
Vi Editor & its different modes
Basic level Scripting and basic knowledge on how to execute jar files from host
Files and directory permissions
Application based scenarios.

The Data Engineering team is one of the core technology teams of Lumiq.ai and is responsible for creating all the Data related products and platforms which scale for any amount of data, users, and processing. The team also interacts with our customers to work out solutions, create technical architectures and deliver the products and solutions.

If you are someone who is always pondering how to make things better, how technologies can interact, how various tools, technologies, and concepts can help a customer or how a customer can use our products, then Lumiq is the place of opportunities.

 

Who are you?

• Enthusiast is your middle name. You know what’s new in Big Data technologies and how things are moving
• Apache is your toolbox and you have been a contributor to open source projects or have discussed the problems with the community on several occasions
• You use cloud for more than just provisioning a Virtual Machine
• Vim is friendly to you and you know how to exit Nano
• You check logs before screaming about an error
• You are a solid engineer who writes modular code and commits in GIT
• You are a doer who doesn’t say “no” without first understanding
• You understand the value of documentation of your work
• You are familiar with Machine Learning Ecosystem and how you can help your fellow Data Scientists to explore data and create production-ready ML pipelines

Experience

• At least 2 years of Data Engineering Experience
• Have interacted with Customers

Must Have Skills

• Amazon Web Services (AWS) - EMR, Glue, S3, RDS, EC2, Lambda, SQS, SES
• Apache Spark
• Python
• Scala
• PostgreSQL
• Git
• Linux

Good to have Skills

• Apache NiFi
• Apache Kafka
• Apache Hive
• Docker
• Amazon Certification

 

 

Job Overview

We are looking for a Data Engineer to join our data team to solve data-driven critical

business problems. The hire will be responsible for expanding and optimizing the existing

end-to-end architecture including the data pipeline architecture. The Data Engineer will

collaborate with software developers, database architects, data analysts, data scientists and platform team on data initiatives and will ensure optimal data delivery architecture is

consistent throughout ongoing projects. The right candidate should have hands on in

developing a hybrid set of data-pipelines depending on the business requirements.

Responsibilities

• Develop, construct, test and maintain existing and new data-driven architectures.
• Align architecture with business requirements and provide solutions which fits best
• to solve the business problems.
• Build the infrastructure required for optimal extraction, transformation, and loading
• of data from a wide variety of data sources using SQL and Azure ‘big data’
• technologies.
• Data acquisition from multiple sources across the organization.
• Use programming language and tools efficiently to collate the data.
• Identify ways to improve data reliability, efficiency and quality
• Use data to discover tasks that can be automated.
• Deliver updates to stakeholders based on analytics.
• Set up practices on data reporting and continuous monitoring
  
  

Required Technical Skills

• Graduate in Computer Science or in similar quantitative area
• 1+ years of relevant work experience as a Data Engineer or in a similar role.
• Advanced SQL knowledge, Data-Modelling and experience working with relational
• databases, query authoring (SQL) as well as working familiarity with a variety of
• databases.
• Experience in developing and optimizing ETL pipelines, big data pipelines, and datadriven
• architectures.
• Must have strong big-data core knowledge & experience in programming using Spark - Python/Scala
• Experience with orchestrating tool like Airflow or similar
• Experience with Azure Data Factory is good to have
• Build processes supporting data transformation, data structures, metadata,
• dependency and workload management.
• Experience supporting and working with cross-functional teams in a dynamic
• environment.
• Good understanding of Git workflow, Test-case driven development and using CICD
• is good to have
• Good to have some understanding of Delta tables It would be advantage if the candidate also have below mentioned experience using
• the following software/tools:
• Experience with big data tools: Hadoop, Spark, Hive, etc.
• Experience with relational SQL and NoSQL databases
• Experience with cloud data services
• Experience with object-oriented/object function scripting languages: Python, Scala, etc.

 

What you need to have:

 

Primary responsibilities:

• Architect, Design and Build high performance Search systems for personalization, optimization, and targeting
• Designing systems with Solr, Akka, Cassandra, Kafka
• Algorithmic development with primary focus Machine Learning
• Working with rapid and innovative development methodologies like: Kanban, Continuous Integration and Daily deployments
• Participation in design and code reviews and recommend improvements
• Unit testing with JUnit, Performance testing and tuning
• Coordination with internal and external teams
• Mentoring junior engineers
• Participate in Product roadmap and Prioritization discussions and decisions
• Evangelize the solution with Professional services and Customer Success teams

 

Position: Data Engineer  
Location: Chennai- Guindy Industrial Estate
Duration: Full time role
Company: Mobile Programming (https://www.mobileprogramming.com/" target="_blank">https://www.mobileprogramming.com/) 
Client Name: Samsung 

We are looking for a Data Engineer to join our growing team of analytics experts. The hire will be
responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing
data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline
builder and data wrangler who enjoy optimizing data systems and building them from the ground up.
The Data Engineer will support our software developers, database architects, data analysts and data
scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout
ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple
teams, systems and products.

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.
 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
 Experience building and optimizing big data ETL pipelines, architectures and data sets.
 Advanced working SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as working familiarity with a variety of databases.
 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 3-6 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: Spark, Kafka, HBase, Hive etc.
 Experience with relational SQL and NoSQL databases
 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, Scala, etc.

Skills: Big Data, AWS, Hive, Spark, Python, SQL