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AppSierra

Senior Data Engineer

6-8 Years
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  • Posted 7 hours ago
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Job Description

Key Responsibilities

  • Design, build, and maintain robust and scalable data pipeline architectures.
  • Assemble large, complex datasets that meet both functional and non-functional business requirements.
  • Identify, design, and implement internal process improvements — including automation of manual workflows, optimization of data delivery, and re-architecting infrastructure for greater scalability and reliability.
  • Design, build, and optimize ETL infrastructure to enable scalable, high-quality data workflows across diverse sources, leveraging SQL and modern data processing frameworks.
  • Build analytics tools that utilize the data pipeline to deliver actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
  • Collaborate with stakeholders across Executive, Product, Data, and Design teams to resolve data-related technical issues and ensure their data infrastructure needs are met.
  • Ensure data integrity, separation, and security across multiple data centers and AWS regions.
  • Create data tools and frameworks to empower analytics and data science teams in building and optimizing products that drive innovation and establish market leadership.
  • Lead and mentor a small team of data engineers, fostering a culture of technical excellence, collaboration, and continuous improvement.
  • Provide technical guidance, set coding standards, conduct code reviews, and support career development for team members.
  • Work closely with data and analytics experts to continually enhance the functionality, reliability, and scalability of our data systems.

Data Engineering And Infrastructure

  • 6+ years of experience in a Data Engineering role, designing, building, and managing scalable and reliable data systems.
  • Proficient with big data and stream-processing technologies such as Spark and Kafka.
  • Hands-on experience with cloud platforms, particularly AWS services like EC2 and RDS.
  • Skilled in building and orchestrating data pipelines using tools like Airflow.
  • Experience with Databricks for scalable data processing and advanced analytics.
  • Strong knowledge of SQLMesh for modern data workflow management.
  • Extensive experience integrating and working with external data sources via REST APIs, GraphQL endpoints, and SFTP servers.
  • Strong communication skills and leadership capabilities are required.

Databases And Data Management

  • Expertise with relational and NoSQL databases, including Postgres and MongoDB.
  • Solid understanding of data modeling, data governance, and data security best practices.

Programming And Development

  • Proficient in Python for data engineering, automation, and workflow scripting.
  • Familiarity with software engineering best practices, including version control, testing, and CI/CD pipelines for data workflows.
  • Experience with JavaScript and TypeScript is a plus.

Analytics, Visualization, And BI

  • Skilled in implementing and supporting self-service BI tools to enable business teams with accessible, actionable insights.
  • Experience with Streamlit for building interactive data visualizations is a plus.

Blockchain And Financial Data Expertise

  • Knowledge of blockchain technology and the cryptocurrency ecosystem is a nice-to- have, with a strong interest in staying up to date with emerging trends.
  • Experience working with financial datasets and financial engineering concepts is considered a strong advantage.

Our Stack

We work with a modern and evolving technology stack, including but not limited to:

  • Cloud Infrastructure: AWS for cloud services and infrastructure management
  • Databases: PostgreSQL for relational data, MongoDB for non-relational (NoSQL) data, and Redis for caching and real-time data management
  • Backend: NestJS (Node.js, TypeScript) and Python for building scalable backend services
  • Frontend: React for web applications, Streamlit for building interactive data visualizations
  • Data Engineering: Airflow and SQLMesh for data pipeline orchestration and modern workflow management
  • Big Data & Processing: Databricks and Kafka for scalable data processing, analytics, and streaming
  • Integrations & APIs: Extensive use of REST APIs, GraphQL, SFTP, and Slack integrations to enable seamless data exchange and operational workflows

Messaging&EventStreaming: Kafkaforreal-timedatapipelinesandevent-driven architectures

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About Company

Job ID: 149375379

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