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Open nowPosted 11 hours ago

Senior Data Engineer

8allocate10 open roles

Where
Remote
Work mode
Remote
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Your applicationOpen nowSenior Data Engineer8allocate · Remote

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The clock on this job

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Share of postings closed within
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  2. 4.5%3 days
  3. 12.4%7 days
  4. 20.0%14 days
  5. 35.5%30 days
  6. 58.6%60 days
This job: posted 11 hours ago

The posting

About the client:

The client is the leading Autonomous Decision Science company providing data-enabled prescriptive and anticipatory analytics and insights for companies across a broad range of industries. They automate a new way of problem-solving and decision-making, going beyond advanced analytics to understand data, perform analytics, generate insights, answer queries, and make decisions at the speed of the market. This powerful capability uniquely enables “End-to-End Value Chain Optimization and Decision-Making” at scale and allows clients to uncover and understand the inter-relationships that lead to innovative new product development and innovation, heightened consumer understanding and targeted marketing, revenue growth tactics, and intelligent demand and supply-chain planning. They help transform market-leading companies into true data-driven digital enterprises.

Timezone requirements: European working hours are okay; the client is in EST, and our team is in Europe.

English: Advanced level.

Requirements:

  • Minimum of 5 years of hands-on experience as a Data Engineer or in a similar position;
  • Minimum of 3 years of commercial experience with Python;
  • Minimum of 3 years of SQL and experience working with relational databases (Postgres preferred; similar OLTP DB is acceptable);
  • Experience with Python 3, Airflow, and Snowflake;
  • Demonstrated knowledge and experience developing data pipelines to automate data processing workflows;
  • Demonstrated experience in data modeling;
  • Demonstrated knowledge of data warehousing, business intelligence, and application data integration solutions;
  • Demonstratable experience in developing applications and services that run on Azure cloud infrastructure;
  • Strong skills with pandas and Pyspark/Spark;
  • Experience with container management and deployment, e.g., Docker and Kubernetes;
  • Excellent problem-solving and communication skills;
  • Ability to thrive in a fast-paced, remote environment;
  • Comfortable with ambiguity with the ability to build structure and take a proactive approach to drive results;
  • Attention to detail – quality and accuracy in deliverables.

The following additional skills would be beneficial:

  • Knowledge of one or more of the following technologies: Data Science, Machine Learning, Natural Language Processing, Business Intelligence, and Data Visualization;
  • Knowledge of statistics and experience using statistical or BI packages for analyzing large datasets (Excel, R, Python, Power BI, Tableau, etc.);
  • Experience with at least one of the following: Databricks, Spark, Hadoop, or Kafka;
  • FastAPI / Flask, or similar web backend framework experience;
  • Experience with some of the following: Celery, RabbitMQ, and ZeroMQ;
  • Other SQL or NoSQL experience: Redis, Elasticsearch, DuckDB, ClickHouse.

What you will do:

The successful candidate will join a diverse team to:

  • Build unique, high-impact business solutions utilizing advanced technologies for use by world-class clients;
  • Create and maintain the underlying data pipeline architecture for the solution offerings from raw client data to final solution output;
  • Create, populate, and maintain data structures for machine learning and other analytics;
  • Use quantitative and statistical methods to derive insights from the data;
  • Combine machine learning, artificial intelligence (ontologies, inference engines, and rules), and natural language processing under a holistic vision to scale and transform businesses across multiple functions and processes.

Responsibilities Include:

  • Create and maintain an optimal data pipeline architecture, incorporating data wrangling and Extract-Transform-Load (ETL) flows;
  • Assemble large, complex data sets to meet analytical requirements – analytics tables, feature-engineering, etc.;
  • Build the infrastructure required for optimal, automated extraction, transformation, and loading of data from a wide variety of data sources using SQL and other ‘big data’ technologies;
  • Build automated analytics tools that utilize the data pipeline to derive actionable insights;
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.;
  • Design and develop data integrations and data quality framework;
  • Develop appropriate testing strategies and reports for the solution as well as data from external sources;
  • Evaluate new technology for use within the projects;
  • Work with the team and client personnel to administer and operate client-specific instances of the offerings;
  • Configure the data pipelines to accommodate client-specific requirements to onboard new clients;
  • Perform regular operations tasks to ingest new and changing data – implement automation where possible;
  • Implement processes and tools to monitor data quality – investigate and remedy any data-related issues in daily solution operations.

Tech stack: a technical stack of the project:

Backend

  • Programming Language: Python 3.11.2 (latest)
  • Package Manager: Poetry
  • Web Framework: FastAPI
  • Object-Relational Mapping (ORM): SQLAlchemy
  • Linting: ruff
  • Code Formatter: isort
  • Testing Framework: pytest
  • Property-based Testing: Hypothesis
  • Database: PostgreSQL

Frontend

  • Programming Language: TypeScript
  • Package Manager: PNPM
  • Framework: React
  • State Management: Zustand
  • Routing: React Router
  • Data Fetching: TanStack Query (successor to react-query)
  • Build Tool: Vite
  • Unit Testing: Vitest
  • Component Testing: React Testing Library
  • End-to-End Testing: Playwright
  • UI Kit (to be determined)
  • Linting: ESLint + typescript-eslint
  • Code Formatting: Prettier

And:

  • Docker and Docker Compose
  • Kubernetes
  • Airflow
  • Azure
  • Snowflake

Benefits from 8allocate:

  • Team & Culture: Team events, offsites, and a culture that keeps people connected.
  • Learning & Development: Budget for courses, certifications, and conferences.
  • Wellbeing: Flexible support in line with company policy, with options to support your physical and mental wellbeing (sport, mental health, or medical insurance).
  • Rest & Recovery: Paid vacation and sick leave.
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