Build and maintain scalable data pipelines, ETL processes, and data platforms to enable analytics and data‑driven products.

Design, develop, and maintain ETL/ELT pipelines for batch and real‑time data ingestion.
Build and optimize data models, schemas, and data warehouses/lakes (Redshift, Snowflake, BigQuery, Azure Synapse).
Implement data transformation, cleansing, and validation logic to ensure accuracy and reliability.
Integrate diverse data sources (databases, APIs, streaming, logs) and maintain connectors.
Collaborate with data scientists, analysts, and product teams to deliver datasets and APIs for analytics and ML.
Ensure data quality, lineage, and governance; implement monitoring, alerting, and observability for pipelines.
Optimize performance and cost of storage and processing; manage partitioning, indexing, and resource usage.
Maintain infrastructure-as-code for data platforms (Terraform, CloudFormation) and automate deployments.
Document data schemas, pipelines, runbooks, and support incident response for data issues.
Participate in architecture reviews, capacity planning, and tech‑debt remediation.

3+ years’ experience in data engineering, ETL, or related software engineering role.
Proficiency with SQL and working knowledge of relational and NoSQL databases.
Experience with cloud platforms and data services (AWS/Azure/GCP).
Familiarity with ETL/ELT tools and frameworks (Airflow, dbt, Spark, Kafka, Flink).
Strong programming skills in Python, Scala, or Java.
Understanding of data modeling, warehousing concepts, and performance tuning.
Experience with data governance, testing, and monitoring tools.
Excellent problem‑solving, collaboration, and communication skills.

Experience with Snowflake, BigQuery, or Redshift; dbt and Apache Spark expertise.
Knowledge of CI/CD for data pipelines and infrastructure-as-code.
Familiarity with GDPR, data privacy, and security best practices.

Job Type: Full-time

Pay: ﷼24.56 - ﷼45.20 per hour

Expected hours: 40 per week

Data Engineer

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