Data Architect

Main Tasks and Responsibilities:

Design and implement scalable, resilient, and secure Big Data architectures.

Configure and manage distributed environments (on‑premises or cloud) for large‑scale data processing.

Develop and maintain data pipelines using Apache Airflow, including complex DAG design, monitoring, and CI/CD best practices.

Build and optimize batch and streaming applications using Apache Spark.

Drive technical decisions related to data storage, processing, governance, and system integration.

Collaborate with engineering, analytics, and business teams to ensure data quality and availability.

Produce clear documentation of architectures, data flows, and technical components.

Technical Skills:

Proven experience as a Big Data Architect or similar senior technical role.

Strong expertise in Apache Spark (PySpark, SQL, performance tuning).

Solid hands‑on experience with Apache Airflow (DAGs, operators, sensors).

Deep understanding of distributed systems, clusters, containerization, and orchestration (Kubernetes is a plus).

Experience configuring Linux environments, networking, security, and automation.

Strong knowledge of Big Data technologies such as Hadoop, Hive, Kafka, Delta Lake, etc.

Experience working with cloud platforms (AWS, Azure, or GCP).

Strong analytical and problem‑solving skills with a focus on scalable solution design.

Nice to have:

Experience with microservices‑based architectures.

Familiarity with CI/CD tools (GitLab, Jenkins, Argo).

Knowledge of relational and NoSQL databases.

Soft Skills:

Strong analytical abilities, able to synthesize all possible details at the same time.

Adaptability skills.

Team spirit.

Client focus.

Seniority Level:

Mid‑Senior level

Employment Type:

Contract

Job Function:

Consulting

Industries:

IT Services and IT Consulting

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