Coursera

1 month ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Build scalable ELT data pipelines and data models that power data-driven decision-making across analytics, AI, and product features. Own enterprise data modeling strategies and help lead governed, well-structured data systems. Create self-serve analytics products from data consumption through discovery and enablement, identify root causes of business trends, and collaborate with data scientists, stakeholders, and engineers to define and govern high-fidelity data. Mentor your team and contribute to data platform frameworks.

Location: India

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Build scalable data models and high-quality ELT pipelines forming the backbone of the core data lake using tools such as Airflow, dbt, Databricks, and BI/visualization tools like Sigma, Looker, and Tableau.
•Create data pipelines and launch self-serve analytics products across data consumption, discovery, and enablement, linking work to business outcomes and root-cause analysis of trends.
•Mentor the team and advocate for stakeholders to increase data literacy, reduce business pain points, and resolve data gaps.
•Partner with data scientists, business stakeholders, and product engineers to define, curate, and govern high-fidelity data and connect KPI relationships to ROI.
•Develop new tools and contribute to data platform frameworks with other engineers, enhancing frameworks with AI-driven capabilities.

Key Requirements

•8+ years in data/analytics engineering with expertise in data architecture, pipelines, and reporting, including relational databases and DRY data modeling practices with efficient SQL code generation.
•Strong experience with AWS and/or Databricks ecosystem tools such as Databricks, Delta Lake, Airflow, dbt, Redshift, and Datahub.
•Hands-on self-serve reporting experience using BI tools such as Looker or Sigma (preferred).
•Experience implementing data observability, quality, and monitoring frameworks/tools at an enterprise level (e.g., dbt tests, Great Expectations, Datadog).
•Strong hands-on experience with AI tools such as Claude, Gemini, and Cursor and how they streamline data processing and support data democratization.

Skills:MentorshipStakeholder managementTechnical communicationInnovationData governance focus

Languages:English

Tech Stack:ELTAirflowDbtDatabricksSigmaLookerTableauAWSDelta LakeRedshiftDatahubBI toolsGreat ExpectationsDatadogSQLPIIData lakesBatch architectureStreaming architecturePyspark

Company Brief

Coursera

Operates an online learning platform offering MOOCs, professional certificates, and degree programs in partnership with universities and organizations worldwide, enabling learners and professionals to acquire new skills and credentials online.

Industry: EdTech

Company Size: Enterprise (1,001+ employees)

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Mountain View, United States

Founded: 2012

Website LinkedIn

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Coursera

1 month ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Location: India

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Build scalable data models and high-quality ELT pipelines forming the backbone of the core data lake using tools such as Airflow, dbt, Databricks, and BI/visualization tools like Sigma, Looker, and Tableau.
•Create data pipelines and launch self-serve analytics products across data consumption, discovery, and enablement, linking work to business outcomes and root-cause analysis of trends.
•Mentor the team and advocate for stakeholders to increase data literacy, reduce business pain points, and resolve data gaps.
•Partner with data scientists, business stakeholders, and product engineers to define, curate, and govern high-fidelity data and connect KPI relationships to ROI.
•Develop new tools and contribute to data platform frameworks with other engineers, enhancing frameworks with AI-driven capabilities.

Key Requirements

•8+ years in data/analytics engineering with expertise in data architecture, pipelines, and reporting, including relational databases and DRY data modeling practices with efficient SQL code generation.
•Strong experience with AWS and/or Databricks ecosystem tools such as Databricks, Delta Lake, Airflow, dbt, Redshift, and Datahub.
•Hands-on self-serve reporting experience using BI tools such as Looker or Sigma (preferred).
•Experience implementing data observability, quality, and monitoring frameworks/tools at an enterprise level (e.g., dbt tests, Great Expectations, Datadog).
•Strong hands-on experience with AI tools such as Claude, Gemini, and Cursor and how they streamline data processing and support data democratization.

Skills:MentorshipStakeholder managementTechnical communicationInnovationData governance focus

Languages:English

Tech Stack:ELTAirflowDbtDatabricksSigmaLookerTableauAWSDelta LakeRedshiftDatahubBI toolsGreat ExpectationsDatadogSQLPIIData lakesBatch architectureStreaming architecturePyspark

Company Brief

Coursera

Industry: EdTech

Company Size: Enterprise (1,001+ employees)

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Mountain View, United States

Founded: 2012

Website LinkedIn