companies uncover the 3% of active buyers in their target market. It evaluates
over 100 billion data points and analyzes factors such as buyer journeys, technology
adoption patterns, and other digital footprints to deliver market & sales intelligence.
Its customers have access to the buying patterns and contact information of
more than 17 million companies and 70 million decision makers across the world.
Role – Data Engineer
Responsibilities
Work in collaboration with the application team and integration team to
design, create, and maintain optimal data pipeline architecture and data
structures for Data Lake/Data Warehouse.
Work with stakeholders including the Sales, Product, and Customer Support
teams to assist with data-related technical issues and support their data
analytics needs.
Assemble large, complex data sets from third-party vendors to meet 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, Elasticsearch,
MongoDB, and AWS technology.
Streamline existing and introduce enhanced reporting and analysis solutions
that leverage complex data sources derived from multiple internal systems.
Requirements
5+ years of experience in a Data Engineer role.
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.
About Series 'A' funded Silicon Valley based BI startup
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prioritization and planning
To work for APAC Chief Data Office and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).
General Skills:
Excellent knowledge of RDBMS and hands-on experience with complex SQL is a must, some experience in NoSQL and Big Data Technologies like Hive and Spark would be a plus
Experience with industrialized reporting on BI tools like PowerBI, Informatica
Knowledge of data related industry best practices in the highly regulated CIB industry, experience with regulatory report generation for financial institutions
Knowledge of industry-leading data access, data security, Master Data, and Reference Data Management, and establishing data lineage
5+ years experience on Data Visualization / Business Intelligence / ETL developer roles
Ability to multi-task and manage various projects simultaneously
Attention to detail
Ability to present to Senior Management, ExCo; excellent written and verbal communication skills
ABOUT EPISOURCE:
Episource has devoted more than a decade in building solutions for risk adjustment to measure healthcare outcomes. As one of the leading companies in healthcare, we have helped numerous clients optimize their medical records, data, analytics to enable better documentation of care for patients with chronic diseases.
The backbone of our consistent success has been our obsession with data and technology. At Episource, all of our strategic initiatives start with the question - how can data be “deployed”? Our analytics platforms and datalakes ingest huge quantities of data daily, to help our clients deliver services. We have also built our own machine learning and NLP platform to infuse added productivity and efficiency into our workflow. Combined, these build a foundation of tools and practices used by quantitative staff across the company.
What’s our poison you ask? We work with most of the popular frameworks and technologies like Spark, Airflow, Ansible, Terraform, Docker, ELK. For machine learning and NLP, we are big fans of keras, spacy, scikit-learn, pandas and numpy. AWS and serverless platforms help us stitch these together to stay ahead of the curve.
ABOUT THE ROLE:
We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations, clinical named entity recognition, improving patient health, clinical suspecting and information extraction from clinical notes.
This is a role for highly technical data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.
You will be responsible for setting an agenda to develop and ship data-driven architectures that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company and help build a foundation of tools and practices used by quantitative staff across the company.
During the course of a typical day with our team, expect to work on one or more projects around the following;
1. Create and maintain optimal data pipeline architectures for ML
2. Develop a strong API ecosystem for ML pipelines
3. Building CI/CD pipelines for ML deployments using Github Actions, Travis, Terraform and Ansible
4. Responsible to design and develop distributed, high volume, high-velocity multi-threaded event processing systems
5. Knowledge of software engineering best practices across the development lifecycle, coding standards, code reviews, source management, build processes, testing, and operations
6. Deploying data pipelines in production using Infrastructure-as-a-Code platforms
7. Designing scalable implementations of the models developed by our Data Science teams
8. Big data and distributed ML with PySpark on AWS EMR, and more!
BASIC REQUIREMENTS
-
Bachelor’s degree or greater in Computer Science, IT or related fields
-
Minimum of 5 years of experience in cloud, DevOps, MLOps & data projects
-
Strong experience with bash scripting, unix environments and building scalable/distributed systems
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Experience with automation/configuration management using Ansible, Terraform, or equivalent
-
Very strong experience with AWS and Python
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Experience building CI/CD systems
-
Experience with containerization technologies like Docker, Kubernetes, ECS, EKS or equivalent
-
Ability to build and manage application and performance monitoring processes
Job Description
Mandatory Requirements
-
Experience in AWS Glue
-
Experience in Apache Parquet
-
Proficient in AWS S3 and data lake
-
Knowledge of Snowflake
-
Understanding of file-based ingestion best practices.
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Scripting language - Python & pyspark
CORE RESPONSIBILITIES
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Create and manage cloud resources in AWS
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Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
-
Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
-
Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
-
Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
-
Define process improvement opportunities to optimize data collection, insights and displays.
-
Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
-
Identify and interpret trends and patterns from complex data sets
-
Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
-
Key participant in regular Scrum ceremonies with the agile teams
-
Proficient at developing queries, writing reports and presenting findings
-
Mentor junior members and bring best industry practices.
QUALIFICATIONS
-
5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
-
Strong background in math, statistics, computer science, data science or related discipline
-
Advanced knowledge one of language: Java, Scala, Python, C#
-
Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
-
Proficient with
-
Data mining/programming tools (e.g. SAS, SQL, R, Python)
-
Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
-
Data visualization (e.g. Tableau, Looker, MicroStrategy)
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Comfortable learning about and deploying new technologies and tools.
-
Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
-
Good written and oral communication skills and ability to present results to non-technical audiences
-
Knowledge of business intelligence and analytical tools, technologies and techniques.
Familiarity and experience in the following is a plus:
-
AWS certification
-
Spark Streaming
-
Kafka Streaming / Kafka Connect
-
ELK Stack
-
Cassandra / MongoDB
-
CI/CD: Jenkins, GitLab, Jira, Confluence other related tools
* Formulates and recommends standards for achieving maximum performance
and efficiency of the DW ecosystem.
* Participates in the Pre-sales activities for solutions of various customer
problem-statement/situations.
* Develop business cases and ROI for the customer/clients.
* Interview stakeholders and develop BI roadmap for success given project
prioritization
* Evangelize self-service BI and visual discovery while helping to automate any
manual process at the client site.
* Work closely with the Engineering Manager to ensure prioritization of
customer deliverables.
* Champion data quality, integrity, and reliability throughout the organization by
designing and promoting best practices.
*Implementation 20%
* Help DW/DE team members with issues needing technical expertise or
complex systems and/or programming knowledge.
* Provide on-the-job training for new or less experienced team members.
* Develop a technical excellence team
Requirements
- experience designing business intelligence solutions
- experience with ETL Process, Data warehouse architecture
- experience with Azure Data services i.e., ADF, ADLS Gen 2, Azure SQL dB,
Synapse, Azure Databricks, and Power BI
- Good analytical and problem-solving skills
- Fluent in relational database concepts and flat file processing concepts
- Must be knowledgeable in software development lifecycles/methodologies
Skills- Informatica with Big Data Management
1.Minimum 6 to 8 years of experience in informatica BDM development
2.Experience working on Spark/SQL
3.Develops informtica mapping/Sql
About Us
Punchh is the leader in customer loyalty, offer management, and AI solutions for offline and omni-channel merchants including restaurants, convenience stores, and retailers. Punchh brings the power of online to physical brands by delivering omni-channel experiences and personalization across the entire customer journey--from acquisition through loyalty and growth--to drive same store sales and customer lifetime value. Punchh uses best-in-class integrations to POS and other in-store systems such as WiFi, to deliver real-time SKU-level transaction visibility and offer provisioning for physical stores.
Punchh is growing exponentially, serves 200+ brands that encompass 91K+ stores globally. Punchh’s customers include the top convenience stores such as Casey’s General Stores, 25+ of the top 100 restaurant brands such as Papa John's, Little Caesars, Denny’s, Focus Brands (5 of 7 brands), and Yum! Brands (KFC, Pizza Hut, and Taco Bell), and retailers. For a multi-billion $ brand with 6K+ stores, Punchh drove a 3% lift in same-store sales within the first year. Punchh is powering loyalty programs for 135+ million consumers.
Punchh has raised $70 million from premier Silicon Valley investors including Sapphire Ventures and Adam Street Partners, has a seasoned leadership team with extensive experience in digital, marketing, CRM, and AI technologies as well as deep restaurant and retail industry expertise.
About the Role:
Punchh Tech India Pvt. is looking for a Senior Data Analyst – Business Insights to join our team. If you're excited to be part of a winning team, Punchh is a great place to grow your career.
This position is responsible for discovering the important trends among the complex data generated on Punchh platform, that have high business impact (influencing product features and roadmap). Creating hypotheses around these trends, validate them with statistical significance and make recommendations
Reporting to: Director, Analytics
Job Location: Jaipur
Experience Required: 4-6 years
What You’ll Do
- Take ownership of custom data analysis projects/requests and work closely with end users (both internal and external clients) to deliver the results
- Identify successful implementation/utilization of product features and contribute to the best-practices playbook for client facing teams (Customer Success)
- Strive towards building mini business intelligence products that add value to the client base
- Represent the company’s expertise in advanced analytics in a variety of media outlets such as client interactions, conferences, blogs, and interviews.
What You’ll Need
- Masters in business/behavioral economics/statistics with a strong interest in marketing technology
- Proven track record of at least 5 years uncovering business insights, especially related to Behavioral Economics and adding value to businesses
- Proficient in using the proper statistical and econometric approaches to establish the presence and strength of trends in data. Strong statistical knowledge is mandatory.
- Extensive prior exposure in causal inference studies, based on both longitudinal and latitudinal data.
- Excellent experience using Python (or R) to analyze data from extremely large or complex data sets
- Exceptional data querying skills (Snowflake/Redshift, Spark, Presto/Athena, to name a few)
- Ability to effectively articulate complex ideas in simple and effective presentations to diverse groups of stakeholders.
- Experience working with a visualization tool (preferably, but not restricted to Tableau)
- Domain expertise: extensive exposure to retail business, restaurant business or worked on loyalty programs and promotion/campaign effectiveness
- Should be self-organized and be able to proactively identify problems and propose solutions
- Gels well within and across teams, work with stakeholders from various functions such as Product, Customer Success, Implementations among others
- As the stakeholders on business side are based out of US, should be flexible to schedule meetings convenient to the West Coast timings
- Effective in working autonomously to get things done and taking the initiatives to anticipate needs of executive leadership
- Able and willing to relocate to Jaipur post pandemic.
Benefits:
- Medical Coverage, to keep you and your family healthy.
- Compensation that stacks up with other tech companies in your area.
- Paid vacation days and holidays to rest and relax.
- Healthy lunch provided daily to fuel you through your work.
- Opportunities for career growth and training support, including fun team building events.
- Flexibility and a comfortable work environment for you to feel your best.
bachelor’s degree or equivalent experience
● Knowledge of database fundamentals and fluency in advanced SQL, including concepts
such as windowing functions
● Knowledge of popular scripting languages for data processing such as Python, as well as
familiarity with common frameworks such as Pandas
● Experience building streaming ETL pipelines with tools such as Apache Flink, Apache
Beam, Google Cloud Dataflow, DBT and equivalents
● Experience building batch ETL pipelines with tools such as Apache Airflow, Spark, DBT, or
custom scripts
● Experience working with messaging systems such as Apache Kafka (and hosted
equivalents such as Amazon MSK), Apache Pulsar
● Familiarity with BI applications such as Tableau, Looker, or Superset
● Hands on coding experience in Java or Scala
Location: Chennai- Guindy Industrial Estate
Duration: Full time role
Company: Mobile Programming (https://www.mobileprogramming.com/" target="_blank">https://www.
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