- Company Name
- Bitfarms
- Job Title
- Ingénieur de Données Senior
- Job Description
-
Job title: Senior Data Engineer
Role Summary: Design, build, and operate a next‑generation data platform for Bitfarms, implementing a scalable data lake architecture, data ingestion/transformation pipelines, and a robust data classification framework aligned with DLP initiatives. Collaborate with business, cybersecurity, and compliance stakeholders to understand, govern, and secure enterprise data assets at scale.
Expectations:
- Deliver high‑availability, performance‑optimized, and cost‑efficient data lake solutions.
- Translate operational, regulatory, and security requirements into scalable data engineering solutions.
- Lead the development of data classification and DLP capability, ensuring compliance with internal and external standards.
- Communicate effectively with cross‑functional teams, translating technical concepts into business value.
Key Responsibilities:
- Design, implement, and maintain an enterprise data lake supporting analytics, reporting, and advanced workloads.
- Define and automate ingestion, transformation, and storage models for structured, semi‑structured, and unstructured data.
- Apply best practices in data modeling, partitioning, query optimization, and cost control.
- Ensure data platform reliability, data quality, and high availability.
- Develop a data classification framework in collaboration with Cybersecurity and Compliance, tagging and managing sensitive data.
- Deploy and support DLP policies that detect, monitor, and protect sensitive data across ecosystems.
- Work closely with stakeholders to capture business requirements, refine data governance policies, and assess impact on system design.
- Continuously assess new technologies and methods to enhance platform capabilities.
Required Skills:
- Deep expertise in data lake architectures (e.g., Delta Lake, LakeHouse, Snowflake, BigQuery, Redshift Spectrum, S3, Azure Data Lake).
- Proficiency in ETL/ELT development using Spark, Flink, or Hadoop ecosystem; experience with streaming (Kafka, Kinesis, Pub/Sub) is a plus.
- Strong programming skills in Python, Scala, or Java; proficiency in SQL and data warehousing concepts.
- Experience with data modeling, partitioning strategies, performance tuning, and cost optimization.
- Knowledge of data governance, lineage, cataloging, and metadata management.
- Familiarity with security best practices: encryption, access controls, compliance frameworks (GDPR, CCPA, ISO/IEC 27001, NIST).
- Experience implementing DLP, data masking, and classification solutions.
- Excellent communication, stakeholder management, and problem‑solving abilities.
- Strong analytical mindset and ability to work in a rapidly evolving technical environment.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Information Systems, or related field; advanced degree preferred.
- Equivalent practical experience in high‑scale data engineering can substitute for formal education.
- Industry certifications (e.g., AWS Certified Big Data – Specialty, Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer) are desirable but not mandatory.