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ਜੌਬਗੈਦਰ

Founding Data Engineer - Analytics Platform

Jobgether

Remote · ਪੂਰਾ ਸਮਾਂ

ਅਰਜ਼ੀ ਦੇਣ ਵਾਲੇ ਪਹਿਲੇ ਵਿਅਕਤੀ ਬਣੋ

ਅਨੁਭਵ
3+ ਸਾਲ
ਤਨਖਾਹ
ਖੁੱਲ੍ਹਣ ਵਾਲੀਆਂ ਥਾਵਾਂ
1
ਪੋਸਟ ਕੀਤਾ ਗਿਆ
3 ਘੰਟੇ
ਕੰਮ ਮੋਡ
ਘਰੋਂ ਕੰਮ ਕਰੋ
ਰੈਜ਼ਿਊਮੇ
ਅਰਜ਼ੀ ਦੇਣ ਲਈ ਲੋੜੀਂਦਾ ਹੈ

ਕੰਮ ਦਾ ਵੇਰਵਾ

Position Overview

A partner company is seeking a Founding Data Engineer to join their technology team remotely from Germany. This role is a remarkable chance to architect and build the foundational elements of a modern data ecosystem that supports analytics, business intelligence, and upcoming AI projects. The engineer will be responsible for designing and scaling a data platform, influencing architectural decisions, engineering norms, and data methodologies in collaboration with leadership and cross-disciplinary teams.

Key Responsibilities

  • Design, develop, and maintain scalable ELT/ETL pipelines integrating data from products, payment gateways, and external APIs.
  • Build and oversee cloud data warehouses using platforms like Snowflake, BigQuery, or Redshift.
  • Develop and manage data workflow orchestration through Airflow, Prefect, Dagster, or similar tools.
  • Optimize data warehouse efficiency including performance, scalability, and cost through robust modeling and query optimization techniques.
  • Create maintainable, testable data transformation workflows with dbt or equivalent frameworks.
  • Implement comprehensive data quality checks, monitoring, lineage tracking, and documentation procedures.
  • Establish secure and privacy-conscious data handling policies, including access management and sensitive data protection.
  • Design semantic layers and unified business metrics to support analytics and organizational decision-making.
  • Collaborate with Product, Growth, and Engineering teams on analytics, reporting, experimentation, event tracking, and API integrations.
  • Champion DataOps practices including CI/CD, version control, automated testing, and documentation standards.
  • Contribute to the ongoing evolution of data strategy and foundational technologies for future AI and machine learning efforts.

Qualifications and Experience

  • Minimum 3 years’ experience in data engineering or a similar role focused on data systems.
  • Advanced proficiency in SQL and Python; Scala knowledge is an advantage.
  • Hands-on experience with cloud-based data warehouses such as Snowflake, BigQuery, or Redshift.
  • Proven track record with production data pipelines and scalable architectures.
  • Experience with orchestration tools including Airflow, Prefect, or Dagster.
  • Strong grasp of data modeling and transformation using dbt or comparable tools.
  • Competence in implementing data quality, monitoring, governance, and documentation.
  • Excellent communication skills to effectively collaborate with diverse teams.
  • A strong sense of ownership focused on reliability and maintainability over time.
  • Familiarity with secure data handling and privacy-focused practices.

Desired Qualifications

  • Experience in B2C SaaS, subscription services, or marketplace business environments.
  • Knowledge of product analytics platforms like Segment, Amplitude, or Mixpanel.
  • Exposure to creating semantic layers or canonical data models.
  • Experience with streaming technologies such as Kafka or Kinesis.
  • Involvement with ML infrastructure, feature stores, or AI-centric data systems.
  • Previous experience in startup or scale-up environments building data platforms.

Benefits and Work Conditions

  • Competitive salary package.
  • Fully remote work with flexible hours.
  • 22 paid leave days plus local public holidays.
  • Opportunity to design and influence a state-of-the-art data platform from inception.
  • High degree of ownership and impact on architecture and engineering practices.
  • Access to contemporary tools and modern engineering workflows.
  • Chance to tackle meaningful technical challenges with business impact.
  • A collaborative, product-driven culture where data is central to decision-making.
  • Professional growth opportunities in a dynamic tech environment.

ਜੇਕਰ ਤੁਸੀਂ ਜਵਾਬ ਚਾਹੁੰਦੇ ਹੋ ਤਾਂ ਇਸਨੂੰ ਛੱਡ ਦਿਓ — ਅਸੀਂ ਇਸਨੂੰ ਕਿਸੇ ਹੋਰ ਚੀਜ਼ ਲਈ ਨਹੀਂ ਵਰਤਾਂਗੇ।

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