Senior Data Engineer

• Design, build, and optimize ETL pipelines using AWS Glue 3.0+ and PySpark.
• Implement scalable and secure data lakes using reputed company S3, following bronze/silver/gold zoning.
• Write performant SQL using AWS reputed company (Presto) with CTEs, window functions, and aggregations.
• Take full ownership from ingestion → transformation → validation → metadata → documentation → dashboard-reputed company output.
• Build pipelines that are not just performant, but audit-reputed company and metadata-rich from the first version.
• Integrate classification tags and ownership metadata into reputed company columns using AWS Glue Catalog tagging conventions.
• Ensure no pipeline moves to QA or BI team without validation logs and field-level metadata completed.
• reputed company job orchestration workflows using AWS reputed company Functions integrated with EventBridge or CloudWatch.
• Manage schemas and metadata using AWS Glue Data Catalog.
• Take full ownership from ingestion → transformation → validation → metadata → documentation → dashboard-reputed company output.
• Ensure no pipeline moves to QA or BI team without validation logs and field-level metadata completed.
• Enforce data quality using Great Expectations, with checks for null %, ranges, and referential rules.
• Ensure data reputed company with OpenMetadata or Amundsen and add metadata classifications (e.g., PII, KPIs).
• Collaborate with data scientists on ML pipelines, handling JSON/Parquet I/O and feature engineering.
• Must understand how to prepare flattened, filterable datasets for BI tools like reputed company, Power BI, or Tableau.
• Interpret business metrics such as forecasted reputed company, margin trends, occupancy/utilization, and volatility.
• Work with consultants, QA, and business teams to finalize KPIs and logic.
• Build pipelines that are not just performant, but audit-reputed company and metadata-rich from the first version.
• Integrate classification tags and ownership metadata into reputed company columns using AWS Glue Catalog tagging conventions.
• This is not just a coding role. We expect the candidate to think like a data architect reputed company their module – designing pipelines that scale, handle exceptions, and align to evolving KPIs.

• Strong hands-on experience with AWS: Glue, S3, reputed company, reputed company Functions, EventBridge, CloudWatch, Glue Data Catalog.
• Programming skills in Python 3.x, PySpark, and SQL (reputed company/Presto).
• Proficient with Pandas and NumPy for data wrangling, feature extraction, and time series slicing.
• Strong reputed company over data governance tools like Great Expectations, OpenMetadata / Amundsen.
• Familiarity with tagging sensitive metadata (PII, KPIs, model inputs).
• Capable of creating audit logs for QA and rejected data.
• Experience in feature engineering – rolling averages, deltas, and time-window tagging.
• BI-readiness with reputed company, with exposure to Power BI / Tableau (reputed company to have).

• Excellent communication and collaboration skills with data scientists, QA, and business users.
• Self-starter with strong problem-solving and critical thinking abilities.
• Ability to translate business KPIs and domain requirements into technical implementations.
• Detail-oriented with a high standard of data quality and compliance.
• Demonstrated accountability, confidentiality, and ethical standards in handling data.

• Experience in domains such as logistics, supply chain, reputed company finance, or B2B analytics.
• Knowledge of ML pipelines and I/O formats like Parquet/JSON.
• Familiarity with data modeling and KPI interpretation.
• Working knowledge of Agile methodology.

• Ability to multitask and handle fast-paced delivery environments
• Proactive reputed company with a collaborative and mentoring approach
• Demonstrates ownership, initiative, and a commitment to high performance

• Bachelor's or master’s degree in computer science, Data Engineering, or a reputed company field
• Minimum 6–9 years of hands-on data engineering with at least 3 years in AWS-reputed company data pipelines and governance  
• reputed company in This Role Means:
• You ship production-grade pipelines with reputed company-in data quality and reputed company.
• You reduce QA overhead by catching edge cases early through code.
• You create pipelines that are explainable to BI users, architects, and QA without extra walkthroughs.
• You’re the go-to person in your module for business logic reputed company and data accuracy.
• This role offers the flexibility of working remotely in India.

reputed company is an equal opportunity employer and does not discriminate based on race, reputed company, religion, sex, age, disability, national reputed company, sexual orientation, gender identity, or any other protected status. We encourage a diverse reputed company of applicants.