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Proficiency in Linux.
Must have SQL knowledge and experience working with relational databases,
query authoring (SQL) as well as familiarity with databases including Mysql,
Mongo, Cassandra, and Athena.
Must have experience with Python/Scala.
Must have experience with Big Data technologies like Apache Spark.
Must have experience with Apache Airflow.
Experience with data pipeline and ETL tools like AWS Glue.
Experience working with AWS cloud services: EC2, S3, RDS, Redshift.
Data Analyst
Job Description
Summary
Are you passionate about handling large & complex data problems, want to make an impact and have the desire to work on ground-breaking big data technologies? Then we are looking for you.
At Amagi, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Would you like to work in a fast-paced environment where your technical abilities will be challenged on a day-to-day basis? If so, Amagi’s Data Engineering and Business Intelligence team is looking for passionate, detail-oriented, technical savvy, energetic team members who like to think outside the box.
Amagi’s Data warehouse team deals with petabytes of data catering to a wide variety of real-time, near real-time and batch analytical solutions. These solutions are an integral part of business functions such as Sales/Revenue, Operations, Finance, Marketing and Engineering, enabling critical business decisions. Designing, developing, scaling and running these big data technologies using native technologies of AWS and GCP are a core part of our daily job.
Key Qualifications
- Experience in building highly cost optimised data analytics solutions
- Experience in designing and building dimensional data models to improve accessibility, efficiency and quality of data
- Experience (hands on) in building high quality ETL applications, data pipelines and analytics solutions ensuring data privacy and regulatory compliance.
- Experience in working with AWS or GCP
- Experience with relational and NoSQL databases
- Experience to full stack web development (Preferably Python)
- Expertise with data visualisation systems such as Tableau and Quick Sight
- Proficiency in writing advanced SQL queries with expertise in performance tuning handling large data volumes
- Familiarity with ML/AÍ technologies is a plus
- Demonstrate strong understanding of development processes and agile methodologies
- Strong analytical and communication skills. Should be self-driven, highly motivated and ability to learn quickly
Description
Data Analytics is at the core of our work, and you will have the opportunity to:
- Design Data-warehousing solutions on Amazon S3 with Athena, Redshift, GCP Bigtable etc
- Lead quick prototypes by integrating data from multiple sources
- Do advanced Business Analytics through ad-hoc SQL queries
- Work on Sales Finance reporting solutions using tableau, HTML5, React applications
We build amazing experiences and create depth in knowledge for our internal teams and our leadership. Our team is a friendly bunch of people that help each other grow and have a passion for technology, R&D, modern tools and data science.
Our work relies on deep understanding of the company needs and an ability to go through vast amounts of internal data such as sales, KPIs, forecasts, Inventory etc. One of the key expectations of this role would be to do data analytics, building data lakes, end to end reporting solutions etc. If you have a passion for cost optimised analytics and data engineering and are eager to learn advanced data analytics at a large scale, this might just be the job for you..
Education & Experience
A bachelor’s/master’s degree in Computer Science with 5 to 7 years of experience and previous experience in data engineering is a plus.

WHAT YOU WILL DO:
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● Create and maintain optimal data pipeline architecture.
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● Assemble large, complex data sets that meet functional / non-functional business requirements.
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● Identify, design, and implement internal process improvements: automating manual processes,
optimizing data delivery, re-designing infrastructure for greater scalability, etc.
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● Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide
variety of data sources using Spark,Hadoop and AWS 'big data' technologies.(EC2, EMR, S3, Athena).
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● Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition,
operational efficiency and other key business performance metrics.
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● Work with stakeholders including the Executive, Product, Data and Design teams to assist with
data-related technical issues and support their data infrastructure needs.
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● Keep our data separated and secure across national boundaries through multiple data centers and AWS
regions.
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● Create data tools for analytics and data scientist team members that assist them in building and
optimizing our product into an innovative industry leader.
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● Work with data and analytics experts to strive for greater functionality in our data systems.
REQUIRED SKILLS & QUALIFICATIONS:
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● 5+ years of experience in a Data Engineer role.
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● Advanced working SQL knowledge and experience working with relational databases, query authoring
(SQL) as well as working familiarity with a variety of databases.
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● Experience building and optimizing 'big data' data pipelines, architectures and data sets.
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● Experience performing root cause analysis on internal and external data and processes to answer
specific business questions and identify opportunities for improvement.
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● Strong analytic skills related to working with unstructured datasets.
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● Build processes supporting data transformation, data structures, metadata, dependency and workload
management.
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● A successful history of manipulating, processing and extracting value from large disconnected datasets.
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● Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
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● Strong project management and organizational skills.
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● Experience supporting and working with cross-functional teams in a dynamic environment
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● Experience with big data tools: Hadoop, Spark, Pig, Vetica, etc.
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● Experience with AWS cloud services: EC2, EMR, S3, Athena
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● Experience with Linux
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● Experience with object-oriented/object function scripting languages: Python, Java, Shell, Scala, etc.
PREFERRED SKILLS & QUALIFICATIONS:
● Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
Experienced in writing complex SQL select queries (window functions & CTE’s) with advanced SQL experience
Should be an individual contributor for initial few months based on project movement team will be aligned
Strong in querying logic and data interpretation
Solid communication and articulation skills
Able to handle stakeholders independently with less interventions of reporting manager
Develop strategies to solve problems in logical yet creative ways
Create custom reports and presentations accompanied by strong data visualization and storytelling
- Hands-on programming expertise in Java OR Python
- Strong production experience with Spark (Minimum of 1-2 years)
- Experience in data pipelines using Big Data technologies (Hadoop, Spark, Kafka, etc.,) on large scale unstructured data sets
- Working experience and good understanding of public cloud environments (AWS OR Azure OR Google Cloud)
- Experience with IAM policy and role management is a plus
Data warehousing architect/ desinger
Data migration architect/ designer
Engineering group to plan ongoing feature development, product maintenance.
• Familiar with Virtualization, Containers - Kubernetes, Core Networking, Cloud Native
Development, Platform as a Service – Cloud Foundry, Infrastructure as a Service, Distributed
Systems etc
• Implementing tools and processes for deployment, monitoring, alerting, automation, scalability,
and ensuring maximum availability of server infrastructure
• Should be able to manage distributed big data systems such as hadoop, storm, mongoDB,
elastic search and cassandra etc.,
• Troubleshooting multiple deployment servers, Software installation, Managing licensing etc,.
• Plan, coordinate, and implement network security measures in order to protect data, software, and
hardware.
• Monitor the performance of computer systems and networks, and to coordinate computer network
access and use.
• Design, configure and test computer hardware, networking software, and operating system
software.
• Recommend changes to improve systems and network configurations, and determine hardware or
software requirements related to such changes.




