Data Engineer
2 days ago
The Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and analytics-ready datasets on modern cloud data platforms. This role enables business teams to generate insights and supports AI-driven analytics delivery, sitting at the intersection of data engineering, BI enablement, and advanced analytics.
Key ResponsibilitiesData Engineering & Platform Development
o Design, build, and maintain scalable ETL/ELT pipelines for structured and semi-structured data.
o Develop and optimize cloud data warehouses or lakehouses (e.g., BigQuery, Snowflake).
o Build reusable data transformation models (SQL, Python, Dataform/dbt).
o Implement data quality, validation, and lineage controls.
o Integrate data from multiple systems (APIs, SaaS, databases, streaming).
o Support ingestion & streaming workloads (e.g., Pub/Sub, Kafka).
o Collaborate with analytics and AI teams to ensure reliable and accessible data for downstream use.
Business Intelligence & Data Enablement
o Build and automate dashboards and reporting pipelines, focusing on Looker Studio.
o Design and maintain semantic layers/data marts optimized for BI workloads.
o Translate business questions into analytical datasets and dashboards.
o Work closely with business stakeholders to define metrics, KPIs, and data models.
o Ensure data accuracy, usability, and performance for reporting and self-service analytics.
Collaboration & Delivery
o Partner with architects, analysts, and AI teams to deliver end-to-end solutions.
o Document pipelines, data models, and processes.
o Participate in code reviews and engineering best practices.
o Provide knowledge sharing and mentorship to junior team members.
[Optional Bonus] Generative AI & Advanced Analytics
o Exposure to GenAI use cases (chatbots, RAG, document Q&A).
o Familiarity with vector DBs (FAISS, Pinecone) and frameworks (LangChain/LangGraph).
o Experience integrating analytics models into Vertex AI/OpenAI pipelines.
RequirementsExperience
o ~5 years of hands-on data engineering or backend data platform experience.
o years working with cloud ecosystems (GCP preferred).
o Demonstrated experience delivering production-grade data pipelines & BI reports.
Technical Skills
o Programming: Proficient in Python and SQL; experience with data transformation and automation scripts.
o Data Platforms: Experience with BigQuery, Snowflake, Redshift, or Databricks.
o Orchestration Tools: Familiar with Airflow, Composer, or dbt/Dataform.
o BI & Visualization: Looker Studio (preferred), Looker, Power BI, Tableau.
o Big Data Frameworks: Exposure to Spark, Beam, or Kafka is an advantage.
o Version Control & CI/CD: Familiarity with Git, Cloud Build, or similar tools.
o Data Governance: Understanding of metadata, lineage, and access control best practices (bonus).
Soft Skills
o Strong analytical and problem-solving skills.
o Good communication and collaboration skills to work with cross-functional teams.
o Proactive, collaborative, and eager to learn—especially in AI & analytics.
Preferred Qualifications
o Bachelor's degree in Computer Science, Engineering, or related field.
o Google Cloud Professional Data Engineer or equivalent cloud certification (preferred).
o Experience contributing to AI/ML or Gen AI projects (nice to have).
o Fluent in English.
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