Data Engineer (Python, DBT, Redshift, SQL)

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Aroha Technologies, is seeking the following. Apply via Dice today!Job Description:Key Responsibilities: Data ProfilingDevelop repeatable Python/SQL scripts to compute column statistics, null/unique distributions, outlier checks, referential integrity, and rule-based quality validations.Generate and publish standardized profiling reports/dashboards for stakeholder review. Data Mapping (S2T)Create and maintain source-to-target mappings for ingestion and transformation layers, capturing business rules, lineage, assumptions, and edge cases.Maintain version control of mapping documents in GitLab. ELT DevelopmentExtract/Load (Mage): Build and operate ingestion pipelines with retries, alerting, schema enforcement, and parameterized environment configurations.Transform (dbt): Develop staging, cleansing, and mart-level models with dbt tests (unique, not_null, accepted_values) and generate documentation. Versioning & CI/CDUtilize GitLab for branching, merge request reviews, linting, dbt tests, and automated CI/CD deployments. Data Quality ManagementImplement and monitor data quality tests at every stage of the pipeline.Track SLAs and enforce merge blocking on failures to prevent regression. Documentation & Hand-offsMaintain runbooks, S2T documents, dbt docs, and pipeline diagrams.Ensure documentation updates within 3 business days of any change. CollaborationPartner with analysts, architects, and QA teams to clarify transformation rules, review designs, and meet acceptance criteria.Requirements:Required Qualifications:3 6+ years of experience in Data Engineering, preferably with offshore/remote delivery exposure.Strong expertise in SQL (advanced queries, window functions, performance tuning) and Python (data processing with Pandas or PySpark).Hands-on experience with Mage orchestration, dbt modeling, and GitLab workflows.Solid understanding of data modeling, lineage tracking, and data quality frameworks.Excellent communication skills and disciplined documentation practices.Preferred Skills:Experience with Snowflake, BigQuery, Redshift, or Azure Synapse.Exposure to PySpark, Databricks, or Airflow.Awareness of BI tools such as Power BI, Tableau, or Looker for downstream analytics integration.