Senior Data Engineer, Redshift, Airflow, dbt

Job not on LinkedIn

🕒 August 21

🇧🇷 Brazil – Remote

⏳ Contract/Temporary

🟠 Senior

🚰 Data Engineer

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Leega

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2010

💼 Consulting

📣 Marketing

🔌 API

Consulting • Marketing • API

Leega is a leading technology solutions provider in Latin America, specializing in data analytics and cloud solutions. As the first company in the region certified by Google Cloud for Data Analytics, Leega offers a range of services including application development, machine learning, and risk management analytics. The firm partners with major cloud services such as AWS and Microsoft Azure to help businesses enhance their data management and transition effectively to the cloud, ultimately driving digital transformation and innovation.

📋 Description

• Design, build, and maintain ingestion and transformation pipelines orchestrated with Apache Airflow, including retries, idempotency, alerting, and SLAs • Develop and evolve dbt transformation models on the data warehouse, organizing staging, intermediate, and marts layers with tests and documentation • Implement ingestion from transactional databases, third-party APIs, regulatory files, and operational spreadsheets • Define and champion the warehouse data model, including keys, grain, historization, and retroactive corrections • Establish distribution, sort, partitioning, and compression standards in MPP/Redshift environments • Lead performance and cost tuning by analyzing query plans, queues/WLM, concurrency, VACUUM/ANALYZE, queries, and materializations • Instrument observability and automated quality controls covering freshness, volume, contracts, and reconciliation • Design data layers and contracts across teams, defining the source of truth and exposure for BI • Ensure lineage, traceability, access controls, sensitivity-based segregation, and compliance with Brazil’s LGPD and industry regulations • Document architectural decisions, maintain the data dictionary, and contribute to code reviews, pair programming, and standards definition • Collaborate with Wealth Management, Sales, Risk, Compliance, and Operations • Serve as a technical reference for mid-level and junior engineers

🎯 Requirements

• 6+ years of experience in data engineering, including at least 2 years with architectural responsibilities • Proven track record of putting an analytical data platform into production and operating it, including incidents, on-call rotations, and real-world consequences • Advanced SQL: window functions, recursive CTEs, execution-plan analysis, and diagnosis of data skew and disk spills • Python applied to data engineering, with modular, testable, version-controlled code, including pandas or polars, type annotations, and automated tests • Apache Airflow in production: DAG authoring, sensors, backfills, dependency management, and failure handling • Cloud-based MPP data warehouse, preferably Redshift; Snowflake, BigQuery, or Databricks also accepted • dbt or an equivalent version-controlled transformation tool, with testing • Dimensional modeling (Kimball), including fact and dimension tables, grain, SCD Types 1 and 2, bridge tables, and snapshots • Git and a code review culture, with CI/CD applied to data • Performance diagnosis, including explaining slow queries and proving fixes with measurable results • Nice to have: experience in financial services, regulatory data, Terraform, AWS services, Iceberg, Delta, lakehouse architectures, Kafka, Debezium, Kinesis, data quality and catalog tools, BI, and significant migrations • Strong numerical accuracy, clear written communication, autonomy, technical leadership, mentoring, and the ability to translate business needs into sustainable data designs

🏖️ Benefits

• Ongoing professional development • Dynamic and collaborative environment • Leega is an inclusive workplace for everyone • Position also open to candidates with disabilities