Data Engineer

Overview:

Data Engineer

This is a unique greenfield opportunity to make foundational decisions, select the technology stack, and design the systems that will power analytics and data-driven decisions across the entire organization. We need a "builder" who thrives in a fast-paced environment, is excited by a blank canvas, and is passionate about creating scalable, reliable data platforms.

What You will Do:

• Architect & Build:

  Design, build, and deploy the company's new data infrastructure from scratch, including data ingestion pipelines (ETL/ELT), data warehousing, and/or a data lake.

• Technology Evaluation:

  Play a key role in evaluating, selecting, and implementing foundational technologies (e.g., cloud data warehouse, orchestration tools, transformation tools).

• Pipeline Development:

  Develop robust, scalable, and automated data pipelines to collect and process data from diverse sources (e.g., application databases, third-party APIs, event streams).

• Data Modeling:

  Collaborate with stakeholders to understand business requirements and design logical and physical data models for the analytical warehouse.

• Foundation Setting:

  Implement frameworks for data quality, monitoring, logging, and alerting to ensure high data reliability and availability.

• Stakeholder Collaboration:

  Work closely with business analysts, data scientists, and department heads to understand their data needs and deliver actionable solutions.

• Documentation:

  Establish and maintain clear documentation for data architecture, pipelines, and processes to build a sustainable data practice.

Required Qualifications:

• Experience:

  2-4 years of hands-on experience in data engineering.

• Proven Builder:

  Demonstrated experience building data pipelines and data warehouses. Experience in a startup or greenfield environment is a significant plus.

• Technical Skills:

• Strong proficiency in

  SQL

  and data modeling.
• Advanced programming skills in

  Python

  (preferred) or another language like Scala/Java.
• Hands-on experience with at least one major

  cloud platform

  (AWS, GCP, or Azure) and its data services (e.g., Redshift, BigQuery, Snowflake, S3, GCS).

Modern Stack Knowledge:

• Experience with data pipeline orchestration tools (e.g.,

  Airflow

  , Dagster, Prefect).
• Experience with modern data transformation tools (e.g.,

  dbt

  , Spark).

• Mindset:

  A

  proactive, self-starting attitude

  is essential. You must be comfortable with ambiguity, able to manage projects independently, and driven to take ownership from concept to completion.

• Communication:

  Strong verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Nice To Have:

• Experience with

  streaming data technologies

  (e.g., Kafka, Kinesis, Pub/Sub).
• Knowledge of

  Infrastructure as Code (IaC)

  tools (e.g., Terraform, CloudFormation).
• Familiarity with containerization (Docker, Kubernetes).
• Experience setting up initial data governance, security, and access control policies.
• Bachelor's or master's degree in computer science, Engineering, or a related field.