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 Job DescriptionPosition: Sr Data Engineer – Databricks & AWS

Experience: 4 - 5 Years

Company Profile:

Exponentia.ai is an AI tech organization with a presence across India, Singapore, the Middle East, and the UK. We are an innovative and disruptive organization, working on cutting-edge technology to help our clients transform into the enterprises of the future. We provide artificial intelligence-based products/platforms capable of automated cognitive decision-making to improve productivity, quality, and economics of the underlying business processes. Currently, we are transforming ourselves and rapidly expanding our business.

Exponentia.ai has developed long-term relationships with world-class clients such as PayPal, PayU, SBI Group, HDFC Life, Kotak Securities, Wockhardt and Adani Group amongst others.

One of the top partners of Cloudera (leading analytics player) and Qlik (leader in BI technologies), Exponentia.ai has recently been awarded the ‘Innovation Partner Award’ by Qlik in 2017.

Get to know more about us on our website: http://www.exponentia.ai/ and Life @Exponentia.

​Role Overview: 

·         A Data Engineer understands the client requirements and develops and delivers the data engineering solutions as per the scope.

·         The role requires good skills in the development of solutions using various services required for data architecture on Databricks Delta Lake, streaming, AWS, ETL Development, and data modeling.

Job Responsibilities

•         Design of data solutions on Databricks including delta lake, data warehouse, data marts and other data solutions to support the analytics needs of the organization.

•         Apply best practices during design in data modeling (logical, physical) and ETL pipelines (streaming and batch) using cloud-based services.

•         Design, develop and manage the pipelining (collection, storage, access), data engineering (data quality, ETL, Data Modelling) and understanding (documentation, exploration) of the data.

•         Interact with stakeholders regarding data landscape understanding, conducting discovery exercises, developing proof of concepts and demonstrating it to stakeholders.

Technical Skills 

•         Has more than 2 Years of experience in developing data lakes, and datamarts on the Databricks platform.

•         Proven skill sets in AWS Data Lake services such as - AWS Glue, S3, Lambda, SNS, IAM, and skills in Spark, Python, and SQL.

•         Experience in Pentaho

•         Good understanding of developing a data warehouse, data marts etc.

•         Has a good understanding of system architectures, and design patterns and should be able to design and develop applications using these principles.

Personality Traits

•         Good collaboration and communication skills

•         Excellent problem-solving skills to be able to structure the right analytical solutions.

•         Strong sense of teamwork, ownership, and accountability

•         Analytical and conceptual thinking 

•         Ability to work in a fast-paced environment with tight schedules.

•         Good presentation skills with the ability to convey complex ideas to peers and management.

Education:

BE / ME / MS/MCA.

LogiNext is looking for a technically savvy and passionate Principle Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.

Responsibilities :

Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties

Requirements:

Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 8 to 10 years of experience in data mining, data modeling, and reporting 5+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experience in leading a team required.

Roles and

Responsibilities

Seeking AWS Cloud Engineer /Data Warehouse Developer for our Data CoE team to

help us in configure and develop new AWS environments for our Enterprise Data Lake,

migrate the on-premise traditional workloads to cloud. Must have a sound

understanding of BI best practices, relational structures, dimensional data modelling,

structured query language (SQL) skills, data warehouse and reporting techniques.

 Extensive experience in providing AWS Cloud solutions to various business

use cases.

 Creating star schema data models, performing ETLs and validating results with

business representatives

 Supporting implemented BI solutions by: monitoring and tuning queries and

data loads, addressing user questions concerning data integrity, monitoring

performance and communicating functional and technical issues.

Job Description: -

This position is responsible for the successful delivery of business intelligence

information to the entire organization and is experienced in BI development and

implementations, data architecture and data warehousing.

Requisite Qualification

Essential

-

AWS Certified Database Specialty or -

AWS Certified Data Analytics

Preferred

Any other Data Engineer Certification

Requisite Experience

Essential 4 -7 yrs of experience

Preferred 2+ yrs of experience in ETL & data pipelines

Skills Required

Special Skills Required

 AWS: S3, DMS, Redshift, EC2, VPC, Lambda, Delta Lake, CloudWatch etc.

 Bigdata: Databricks, Spark, Glue and Athena

 Expertise in Lake Formation, Python programming, Spark, Shell scripting

 Minimum Bachelor’s degree with 5+ years of experience in designing, building,

and maintaining AWS data components

 3+ years of experience in data component configuration, related roles and

access setup

 Expertise in Python programming

 Knowledge in all aspects of DevOps (source control, continuous integration,

deployments, etc.)

 Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD

 Hands on ETL development experience, preferably using or SSIS

 SQL Server experience required

 Strong analytical skills to solve and model complex business requirements

 Sound understanding of BI Best Practices/Methodologies, relational structures,

dimensional data modelling, structured query language (SQL) skills, data

warehouse and reporting techniques

Preferred Skills

Required

 Experience working in the SCRUM Environment.

 Experience in Administration (Windows/Unix/Network/Database/Hadoop) is a

plus.

 Experience in SQL Server, SSIS, SSAS, SSRS

 Comfortable with creating data models and visualization using Power BI

 Hands on experience in relational and multi-dimensional data modelling,

including multiple source systems from databases and flat files, and the use of

standard data modelling tools

 Ability to collaborate on a team with infrastructure, BI report development and

business analyst resources, and clearly communicate solutions to both

technical and non-technical team members

Job Description

This requirement is to service our client which is a leading big data technology company that measures what viewers consume across platforms to enable marketers make better advertising decisions. We are seeking a Senior Data Operations Analyst to mine large-scale datasets for our client. Their work will have a direct impact on driving business strategies for prominent industry leaders. Self-motivation and strong communication skills are both must-haves. Ability to work in a fast-paced work environment is desired.

Problems being solved by our client: 

Measure consumer usage of devices linked to the internet and home networks including computers, mobile phones, tablets, streaming sticks, smart TVs, thermostats and other appliances. There are more screens and other connected devices in homes than ever before, yet there have been major gaps in understanding how consumers interact with this technology. Our client uses a measurement technology to unravel dynamics of consumers’ interactions with multiple devices.

Duties and responsibilities:

• The successful candidate will contribute to the development of novel audience measurement and demographic inference solutions. 
• Develop, implement, and support statistical or machine learning methodologies and processes. 

• Build, test new features and concepts and integrate into production process
• Participate in ongoing research and evaluation of new technologies
• Exercise your experience in the development lifecycle through analysis, design, development, testing and deployment of this system
• Collaborate with teams in Software Engineering, Operations, and Product Management to deliver timely and quality data. You will be the knowledge expert, delivering quality data to our clients

Qualifications:

• 3-5 years relevant work experience in areas as outlined below
• Experience in extracting data using SQL from large databases
• Experience in writing complex ETL processes and frameworks for analytics and data management. Must have experience in working on ETL tools.

• Master’s degree or PhD in Statistics, Data Science, Economics, Operations Research, Computer Science, or a similar degree with a focus on statistical methods. A Bachelor’s degree in the same fields with significant, demonstrated professional research experience will also be considered. 
• Programming experience in scientific computing language (R, Python, Julia) and the ability to interact with relational data (SQL, Apache Pig, SparkSQL). General purpose programming (Python, Scala, Java) and familiarity with Hadoop is a plus.  
• Excellent verbal and written communication skills. 
• Experience with TV or digital audience measurement or market research data is a plus. 
• Familiarity with systems analysis or systems thinking is a plus. 

• Must be comfortable with analyzing complex, high-volume and high-dimension data from varying sources
• Excellent verbal, written and computer communication skills
• Ability to engage with Senior Leaders across all functional departments
• Ability to take on new responsibilities and adapt to changes