• Developing, maintaining, and monitoring of data and ML pipelines
• Extracting features from Avast data relevant to modeling tasks
• Data analysis on what is behind or what is driving some business phenomenon
• Analysis and modeling in Python
• Building, maintaining, and monitoring of data pipelines (ETLs)
• Coding skills (such as Python, Java, Scala,...)
• Good knowledge of big data systems - Hive, Spark, no-SQL databases,...
• Analyzing big data and knowing any data analysis stack like Python or R
• Ensure high throughput of development teams by identifying potential issues, removing impediments 
• Guiding the team to remove impediments by collaborating with the appropriate resource 
• Enabling real-time analytics and event-driven architecture 
• Develop pipelines for real-time streaming from different sources like FTP, Windows Blob Storage, SQL Server, Cosmos or Mongo DB and 

Skills: Data Engineering and Pipeline Management, Programming Proficiency, Big Data Technologies Expertise, Feature Extraction and Data Analysis, Real-time Data Processing, Analytical Tools Proficiency, Team Leadership and Agile Practices, Event-driven Architecture and Analytics

• Provide data engineering support for key data science projects and use cases run by the Analytics Centre of Excellence
• Responsible for ETL activities by abstracting very technical records of network data into ready-to-use, meaningful
• Understand business-oriented network information for the purpose of network planning and monetization.
• Translates complex functional and technical requirements into detailed design and high-performing data applications.
• Works with data scientists and analysts to make sure all data solutions are consistent.
• Identify new/efficient way to ingest and combine telco and external data such as social media, geospatial and web logs. 
• Design efficient data marts for analytics needs. 
• Constructs and implements operational data stores and data marts.
• Discover and implement new ways to use ETL/ open source tools (e.g. Kafka, Nifi etc.) to ingest structured and unstructured data. 
• Optimize strategies to handle large volumes of batch and streaming data.  
• Ensure data integrity and quality and execute data smoothing/cleansing when deemed necessary  
• Promote common design and best practices, and ensure compliance to standards set by the organization. 

Skills: Data Engineering and ETL Expertise, Data Integration, Database Design and Management, Technical Requirement Translation, Collaboration with Data Teams, Proficiency with Open Source Tools, Data Quality Assurance, Promotion of Best Practices and Compliance

• Define and evangelize the short- and long-term vision on Big Data architecture in light of the increasing strategic importance and value of data within the company.
• Strike the right balance in the way data governance and information architecture is conducted for small- and large-scale data assets (i.e. level of automation, level of detail, coverage, long-term vs short-term focus, cost).
• Identify opportunities for unlocking business value from (integrating) Telenet’s data sources cross-departmentally.
• Collaborate with IT security and legal/compliance teams for similar deliverables on data security, privacy (GDPR) and compliance front.
• Design system architectures for real-time cost-effective (large-scale) data processing and routing.
• Proactively identify techniques that make data assets easier to use or find.
• Democratize access to (large-scale) information assets for business users.
• Working with NoSQL databases such as MongoDB or Cosmos DB 
• Build Python scripts for scheduling, monitoring, & management 
• Ensures database changes are reviewed and approved according to database design standards and principles.
• Coordinate/ partially manage external parties (e.g. Vendors, consultants) who support to generation analysis and projects run by the Analytics Centre of Excellence
• Understanding of big data pipelines 

Skills: Big Data Architecture Design, Information Architecture, Cross-Departmental Data Integration, Data Security and Compliance, Data Accessibility and Democratization, , Programming and Automation

• Build data systems and pipelines to process high volumes of semi-structured and structured data.
• Explore ways to enhance data quality and reliability
• Work closely with the data scientists to develop data models and pipelines for research, reporting, and machine learning
• Use agile software development processes to iteratively make improvements to Nativo's data processing systems
• Build data pipelines that clean, transform, and aggregate data from disparate sources
• Make an immediate impact on product by getting involved early
• Influence many aspects of business through architecting data processing platform. 
• Tangible impact on product and work on projects that are pivotal to team’s success and company’s growth.
• Design and build a self-serving data platform to handle new products and business requirements that securely scale over millions of users and transactions
• Develop, integrate and optimize end to end data pipeline
• Partner with data scientists, data analysts and domain engineering teams to identify and execute on new opportunities.

Skills: Data Engineering and Pipeline Construction, Data Quality Improvement, Collaboration with Data Scientists, Agile Development Practices, Data Integration from Disparate Sources, System Design and Scalability, Cross-functional Partnerships, Impact and Leadership in Projects

• Migrate and ingest data from many data sources including legacy platforms.
• Develop and implement data flows and pipelines into various consumers and 3rd party tools.
• Implement data normalization and transformation algorithms ensuring data consistency and searchability
• Build large-scale batch and real-time data pipelines with data processing frameworks such as Spark on AWS infrastructure
• Utilize cloud-based RDBMS and NoSQL databases services such as Snowflake and RedShift.
• Implement unit tests and conduct code reviews with other team members to ensure code is properly designed, developed for scale and tuned for performance needs.
• Collaborate closely with other data engineers, engineering managers and product owners and deliver cloud-based data solutions that meet marketing and sales objectives.
• Enable company-wide engineering teams to integrate new data pipelines and extend product capabilities through analytics
• Build, maintain, and execute ETL pipelines to process data and store it in a data warehouse system making it accessible to stakeholders
• Develop and maintain globally available APIs and services on GCP
• Promote engineering best practices and site reliability engineering principles and help peers to learn and improve

Skills: Data Pipeline Development, Data Processing Frameworks, Database Management, Data Transformation and Normalization, Software Engineering Practices, Collaboration and Communication, ETL Development, API Development and Management

• Extensive understanding of Web design & programming
• Deep expertise with Spark, Hive, and Google Cloud Platform
• Experience in test automation development or a combination of development and testing experience using HP Quick Test Professional, Selenium Web driver, or similar automation tools
• Experience in creating and maintaining automation scripts to ensure information systems services and programs meet acceptance criteria.
• Should be strong in SQL, PL/SQL and Expert Python Programming
• Provide technical support to delivery teams which may include testing and creation of utilities to support testing.
• Plans and executes automation tasks and ensures testing standards are followed within the team.
• Ability to work independently within a quickly changing environment with strict deadlines
• Ability to multi-task and Strong attention to detail
• Proven communication and documentation skills

Qualifications: BS in Computer Science with 2 years of Experience

• Work creatively and efficiently in troubleshooting and resolution of system issues.
• Excellent organizational, troubleshooting and analytical skills required
• Knowledge of all aspects of the software development life cycle
• Must have experience creating and using RESTful APIs for enterprise applications (JSON, REST)
• Experience in a modern web framework like Angular, React, etc.
• Working knowledge of Postgres or SQL Server
• Experience developing in a fast-paced environment with short production timelines
• Experience in writing unit tests for robustness, including edge cases, usability, and general reliability
• Proven ability to create working prototypes
• Experience with the latest trends in cloud computing, distributed systems, web technologies and UI/UX standards
• Experience in OAuth (SAML 2.0)  and strong analytical skills

Qualifications: BA in Information Technology with 4 years of Experience

• Experience in software development
• Experience working with Big Data Technologies
• Hands-on experience with Hadoop Design and Development work
• Hands-on experience with AWS technologies with at least 1-2 years on EMR
• Experience with developer tools such as Git, SVN, and Maven
• Should have hands-on working experience with RDBMS/SQL and schema design
• Strong written and communication skills
• Expertise in Agile delivery and Networking (DNS, Firewall)
• Continuous Integration and Continuous Delivery Experience
• Experience and understanding of the following core components of AWS (client, storage, compute, virtualization, CloudWatch, Lambda, VPC, Security Roles [IAM], Cloud Formation, Redshift)
• Experience implementing Data strategies tailored to cloud and hybrid cloud implementations
• Experience with complex data models supporting multi-faceted business process

Qualifications: BS in Data Science with 4 years of Experience

• Experience in financial services industry products and regulatory development.
• Solid working experience in various forms of data infrastructure inclusive of RDBMS, such as SQL, Hadoop, Spark, Java, Unix, Oracle and OBIEE
• Professional experience in Data Engineering and Business Intelligence
• Experience in Advanced SQL (analytical functions), RDBMS, ETL, and Data warehousing.
• Advanced data analysis skills
• Strong knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT
• Experience in reporting/analytic tools and environments, data structures, data modeling and performance tuning.
• Ability to effectively communicate with both business and technical teams
• Experience with AWS Glue, Redshift, Lambda, S3, data pipeline, node.js and Python
• Good to have knowledge on CloudBees, AWS Event Bridge and Okta

Qualifications: BA in Statistics with 3 years of Experience

• Experience in Data Engineering and Business Intelligence
• Hands-on experience in writing complex, highly optimized SQL queries across large data sets.
• Strong knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT
• Strong knowledge of reporting/analytic tools and environments, data structures, data modeling, and performance tuning.
• Advanced data analysis skills
• Experience with AWS services including S3, Redshift, EMR
• Knowledge of distributed systems as it pertains to data storage and computing
• Ability to effectively communicate with both business and technical teams.
• Experience on working with Big Data
• Knowledge of Map Reduce, Spark and Presto
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering
• Knowledge of software engineering best practices across the development life-cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

Qualifications: BS in Software Engineering with 7 years of Experience