Data Scientist

Publicis Sapient Overview:

The Senior Associate People Senior Associate L1 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution 

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Job Summary:

As Senior Associate L2 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution

The role requires a hands-on technologist who has strong programming background like Java / Scala / Python, should have experience in Data Ingestion, Integration and data Wrangling, Computation, Analytics pipelines and exposure to Hadoop ecosystem components. You are also required to have hands-on knowledge on at least one of AWS, GCP, Azure cloud platforms.

Role & Responsibilities:

Your role is focused on Design, Development and delivery of solutions involving:

• Data Integration, Processing & Governance

• Data Storage and Computation Frameworks, Performance Optimizations

• Analytics & Visualizations

• Infrastructure & Cloud Computing

• Data Management Platforms

• Implement scalable architectural models for data processing and storage

• Build functionality for data ingestion from multiple heterogeneous sources in batch & real-time mode

• Build functionality for data analytics, search and aggregation

Experience Guidelines:

Mandatory Experience and Competencies:

# Competency

1.Overall 5+ years of IT experience with 3+ years in Data related technologies

2.Minimum 2.5 years of experience in Big Data technologies and working exposure in at least one cloud platform on related data services (AWS / Azure / GCP)

3.Hands-on experience with the Hadoop stack – HDFS, sqoop, kafka, Pulsar, NiFi, Spark, Spark Streaming, Flink, Storm, hive, oozie, airflow and other components required in building end to end data pipeline.

4.Strong experience in at least of the programming language Java, Scala, Python. Java preferable

5.Hands-on working knowledge of NoSQL and MPP data platforms like Hbase, MongoDb, Cassandra, AWS Redshift, Azure SQLDW, GCP BigQuery etc

6.Well-versed and working knowledge with data platform related services on at least 1 cloud platform, IAM and data security

Preferred Experience and Knowledge (Good to Have):

# Competency

1.Good knowledge of traditional ETL tools (Informatica, Talend, etc) and database technologies (Oracle, MySQL, SQL Server, Postgres) with hands on experience

2.Knowledge on data governance processes (security, lineage, catalog) and tools like Collibra, Alation etc

3.Knowledge on distributed messaging frameworks like ActiveMQ / RabbiMQ / Solace, search & indexing and Micro services architectures

4.Performance tuning and optimization of data pipelines

5.CI/CD – Infra provisioning on cloud, auto build & deployment pipelines, code quality

6.Cloud data specialty and other related Big data technology certifications

Personal Attributes:

• Strong written and verbal communication skills

• Articulation skills

• Good team player

• Self-starter who requires minimal oversight

• Ability to prioritize and manage multiple tasks

• Process orientation and the ability to define and set up processes

Role: Principal Software Engineer

We looking for a passionate Principle Engineer - Analytics to build data products that extract valuable business insights for efficiency and customer experience. This role will require managing, processing and analyzing large amounts of raw information and in scalable databases. This will also involve developing unique data structures and writing algorithms for the entirely new set of products. The candidate will be required to have critical thinking and problem-solving skills. The candidates must be experienced with software development with advanced algorithms and must be able to handle large volume of data. Exposure with statistics and machine learning algorithms is a big plus. The candidate should have some exposure to cloud environment, continuous integration and agile scrum processes.

Responsibilities:

• Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule

• Software Development that creates data driven intelligence in the products which deals with Big Data backends

• Exploratory analysis of the data to be able to come up with efficient data structures and algorithms for given requirements

• The system may or may not involve machine learning models and pipelines but will require advanced algorithm development

• Managing, data in large scale data stores (such as NoSQL DBs, time series DBs, Geospatial DBs etc.)

• Creating metrics and evaluation of algorithm for better accuracy and recall

• Ensuring efficient access and usage of data through the means of indexing, clustering etc.

• Collaborate with engineering and product development teams.

Requirements:

• Master’s or Bachelor’s degree in Engineering in one of these domains - Computer Science, Information Technology, Information Systems, or related field from top-tier school

• OR Master’s degree or higher in Statistics, Mathematics, with hands on background in software development.

• Experience of 8 to 10 year with product development, having done algorithmic work

• 5+ years of experience working with large data sets or do large scale quantitative analysis

• Understanding of SaaS based products and services.

• Strong algorithmic problem-solving skills

• Able to mentor and manage team and take responsibilities of team deadline.

Skill set required:

• In depth Knowledge Python programming languages

• Understanding of software architecture and software design

• Must have fully managed a project with a team

• Having worked with Agile project management practices

• Experience with data processing analytics and visualization tools in Python (such as pandas, matplotlib, Scipy, etc.)

• Strong understanding of SQL and querying to NoSQL database (eg. Mongo, Casandra, Redis

DATA ENGINEER

Overview

They started with a singular belief - what is beautiful cannot and should not be defined in marketing meetings. It's defined by the regular people like us, our sisters, our next-door neighbours, and the friends we make on the playground and in lecture halls. That's why we stand for people-proving everything we do. From the inception of a product idea to testing the final formulations before launch, our consumers are a part of each and every process. They guide and inspire us by sharing their stories with us. They tell us not only about the product they need and the skincare issues they face but also the tales of their struggles, dreams and triumphs. Skincare goes deeper than skin. It's a form of self-care for many. Wherever someone is on this journey, we want to cheer them on through the products we make, the content we create and the conversations we have. What we wish to build is more than a brand. We want to build a community that grows and glows together - cheering each other on, sharing knowledge, and ensuring people always have access to skincare that really works.

Job Description:

We are seeking a skilled and motivated Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, developing, and maintaining the data infrastructure and systems that enable efficient data collection, storage, processing, and analysis. You will collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to implement data pipelines and ensure the availability, reliability, and scalability of our data platform.

Responsibilities:

Design and implement scalable and robust data pipelines to collect, process, and store data from various sources.

Develop and maintain data warehouse and ETL (Extract, Transform, Load) processes for data integration and transformation.

Optimize and tune the performance of data systems to ensure efficient data processing and analysis.

Collaborate with data scientists and analysts to understand data requirements and implement solutions for data modeling and analysis.

Identify and resolve data quality issues, ensuring data accuracy, consistency, and completeness.

Implement and maintain data governance and security measures to protect sensitive data.

Monitor and troubleshoot data infrastructure, perform root cause analysis, and implement necessary fixes.

Stay up-to-date with emerging technologies and industry trends in data engineering and recommend their adoption when appropriate.

Qualifications:

Bachelor’s or higher degree in Computer Science, Information Systems, or a related field.

Proven experience as a Data Engineer or similar role, working with large-scale data processing and storage systems.

Strong programming skills in languages such as Python, Java, or Scala.

Experience with big data technologies and frameworks like Hadoop, Spark, or Kafka.

Proficiency in SQL and database management systems (e.g., MySQL, PostgreSQL, or Oracle).

Familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery).

Solid understanding of data modeling, data warehousing, and ETL principles.

Knowledge of data integration techniques and tools (e.g., Apache Nifi, Talend, or Informatica).

Strong problem-solving and analytical skills, with the ability to handle complex data challenges.

Excellent communication and collaboration skills to work effectively in a team environment.

Preferred Qualifications:

Advanced knowledge of distributed computing and parallel processing.

Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Apache Flink).

Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).

Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).

Experience with data visualization and reporting tools (e.g., Tableau, Power BI).

Certification in relevant technologies or data engineering disciplines.

The Data Engineer would be responsible for selecting and integrating Big Data tools and frameworks required. Would implement Data Ingestion & ETL/ELT processes

Required Experience, Skills and Qualifications:

• Hands on experience on Big Data tools/technologies like Spark,  Databricks, Map Reduce, Hive, HDFS.
• Expertise and excellent understanding of big data toolset such as Sqoop, Spark-streaming, Kafka, NiFi
• Proficiency in any of the programming language: Python/ Scala/  Java with 4+ years’ experience
• Experience in Cloud infrastructures like MS Azure, Data lake etc
• Good working knowledge in NoSQL DB (Mongo, HBase, Casandra)

High Level Scope of Work :

• Work with AI / Analytics team to priorities MACHINE LEARNING Identified USE CASES for Development and Rollout
• Meet and understand current retail / Marketing Requirements and how AI/ML solution will address and automate the decision process.
• Develop AI/ML Programs using DATAIKU Solution & Python or open source tech with focus to deliver high Quality and accurate ML prediction Model
• Gather additional and external data sources to support the AI/ML Model as desired .
• Support the ML Model and FINE TUNEit to ensure high accuracy all the time.
• Example of use cases (Customer Segmentation , Product Recommendation, Price Optimization, Retail Customer Personalization Offers, Next Best Location for Business Est, CCTV Computer Vision, NLP and Voice Recognition Solutions)

Required technology expertise :

• Deep Knowledge & Understanding on MACHINE LEARNING ALGORITHMS (Supervised / Unsupervised Learning / Deep Learning Models)
• Hands on EXP for at least 5+ years with PYTHON and R STATISTICS PROGRAMMING Languages
• Strong Database Development knowledge using SQL and PL/SQL
• Must have EXP using Commercial Data Science Solution particularly DATAIKU and (Altryx, SAS, Azure ML, Google ML, Oracle ML is a plus)
• Strong hands on EXP with BIG DATA Solution Architecture and Optimization for AI/ML Workload.
• Data Analytics and BI Tools Hand on EXP particularly (Oracle OBIEE and Power BI)
• Have implemented and Developed at least 3 successful AI/ML Projects with tangible Business Outcomes In retail Focused Industry
• Have at least 5+ Years EXP in Retail Industry and Customer Focus Business.
• Ability to communicate with Business Owner & stakeholders to understand their current issues and provide MACHINE LEARNING Solution accordingly.

Qualifications

• Bachelor Degree or Master Degree in Data Science, Artificial Intelligent, Computer Science
• Certified as DATA SCIENTIST or MACHINE LEARNING Expert.

Data Platform engineering at Uber is looking for a strong Technical Lead (Level 5a Engineer) who has built high quality platforms and services that can operate at scale. 5a Engineer at Uber exhibits following qualities: 

• Demonstrate tech expertise › Demonstrate technical skills to go very deep or broad in solving classes of problems or creating broadly leverageable solutions. 
• Execute large scale projects › Define, plan and execute complex and impactful projects. You communicate the vision to peers and stakeholders.
• Collaborate across teams › Domain resource to engineers outside your team and help them leverage the right solutions. Facilitate technical discussions and drive to a consensus.
• Coach engineers › Coach and mentor less experienced engineers and deeply invest in their learning and success. You give and solicit feedback, both positive and negative, to others you work with to help improve the entire team.
• Tech leadership › Lead the effort to define the best practices in your immediate team, and help the broader organization establish better technical or business processes.

What You’ll Do

• Build a scalable, reliable, operable and performant data analytics platform for Uber’s engineers, data scientists, products and operations teams.
• Work alongside the pioneers of big data systems such as Hive, Yarn, Spark, Presto, Kafka, Flink to build out a highly reliable, performant, easy to use software system for Uber’s planet scale of data. 
• Become proficient of multi-tenancy, resource isolation, abuse prevention, self-serve debuggability aspects of a high performant, large scale, service while building these capabilities for Uber's engineers and operation folks.

What You’ll Need

• 7+ years experience in building large scale products, data platforms, distributed systems in a high caliber environment.
• Architecture: Identify and solve major architectural problems by going deep in your field or broad across different teams. Extend, improve, or, when needed, build solutions to address architectural gaps or technical debt.
• Software Engineering/Programming: Create frameworks and abstractions that are reliable and reusable. advanced knowledge of at least one programming language, and are happy to learn more. Our core languages are Java, Python, Go, and Scala.
• Data Engineering: Expertise in one of the big data analytics technologies we currently use such as Apache Hadoop (HDFS and YARN), Apache Hive, Impala, Drill, Spark, Tez, Presto, Calcite, Parquet, Arrow etc. Under the hood experience with similar systems such as Vertica, Apache Impala, Drill, Google Borg, Google BigQuery, Amazon EMR, Amazon RedShift, Docker, Kubernetes, Mesos etc.
• Execution & Results: You tackle large technical projects/problems that are not clearly defined. You anticipate roadblocks and have strategies to de-risk timelines. You orchestrate work that spans multiple teams and keep your stakeholders informed.
• A team player: You believe that you can achieve more on a team that the whole is greater than the sum of its parts. You rely on others’ candid feedback for continuous improvement.
• Business acumen: You understand requirements beyond the written word. Whether you’re working on an API used by other developers, an internal tool consumed by our operation teams, or a feature used by millions of customers, your attention to details leads to a delightful user experience.