Data Engineer

About Sleek: Sleek is an innovative, fast-scaling fintech pioneer and proudly certified B Corp on a mission to make back-office operations effortlessly simple for micro-SMEs and entrepreneurs worldwide. Launched in 2017 and backing over 15,000 corporate customers across Singapore, Hong Kong, Australia, and the UK, Sleek automates corporate secretary functions, handles digital banking setups, and redefines bookkeeping through its proprietary AI-driven ledger platform, SleekBooks. Backed by world-class investors and securing over 70% compound annual revenue growth, Sleek is recognized by Forbes and LinkedIn as a tech-enabled unicorn in the making.

Position Overview

We are looking for a skilled and passionate Data Engineer to join our growing Data Platform team. In this hands-on engineering track, you will take ownership of designing, implementing, and optimizing robust data pipelines on Databricks and AWS infrastructure to power advanced analytics, reporting, and product intelligence across the organization. Moving beyond basic query handling, you will build scalable ETL/ELT pipelines using both batch and streaming patterns, configure automated ingestion connectors, and design multi-layered data warehousing models. This role demands an automated mindset and structural expertise running modern orchestration engines inside containerized cloud environments.

Key Responsibilities

• Scalable Pipeline Engineering: Architect and implement robust ETL/ELT data pipelines supporting real-time streaming and high-volume batch processing layers.
• Lakehouse Infrastructure Optimization: Build, manage, and optimize modern data workloads inside the Databricks Lakehouse platform leveraging PySpark or Spark SQL.
• Modular Data Transformation: Develop testable, modular data transformations via dbt (data build tool), structuring data warehouses into clear staging, intermediate, and marts layers.
• Workflow DAG Orchestration: Program, schedule, and maintain complex data ingestion workflows and Directed Acyclic Graphs (DAGs) utilizing Apache Airflow.
• Ingestion & CDC Deployment: Configure source-to-destination data connectors using Airbyte, implementing Change Data Capture (CDC), full-load, and incremental ingestion strategies.
• Containerization & Cloud Controls: Deploy and scale core data services inside Docker and Amazon EKS (Elastic Kubernetes Service), utilizing AWS infrastructure features (S3, Lambda, IAM, and CloudWatch).
• Data Platform Quality Assurance: Enforce data platform observability, write automated dbt schema tests, execute source freshness checks, and construct descriptive data dictionaries.

Required Skills & Experience

• 3+ years of verified professional history running enterprise Data Engineering, big data manipulation, or pipeline architecture tracks.
• Deep structural understanding of modern data topologies, including Lakehouse, Data Warehouse, and Data Lake design patterns.
• Hands-on production history authoring, debugging, and maintaining data workflows within Apache Airflow and Airbyte.
• Strong background utilizing Databricks platforms, including Delta Lake features (ACID transactions, time travel, schema evolution).
• Advanced operational SQL mechanics, including complex window functions, Common Table Expressions (CTEs), and query optimization practices.
• Proven background running data modeling loops via **dbt** paired with automated test assertions.
• Familiarity navigating cloud primitives natively within the Amazon Web Services (AWS) console layer.
• Location Context: 100% remote-first full-time operational framework restricted exclusively to qualified data engineers permanently residing inside India or the Philippines.

Preferred Strategic Indicators (Nice to Have)

• Prior experience deploying or executing Apache Airflow and Airbyte instances directly on top of Kubernetes (EKS) clusters.
• Familiarity with programmatic automated data quality validation frameworks such as Great Expectations or Soda.
• Basic automation or pipeline helper scripting experience using Python.
• Exposure to enterprise data governance architectures or asset tracking tools like Databricks Unity Catalog.
• Familiarity deploying software tracking trees via Git and cloud CI/CD systems like GitHub Actions.

What We Offer

• The exceptional engineering runway to build and scale the unified data platform backing a high-growth certified B Corp fintech unicorn.
• Highly competitive local market compensation salary packages supplemented by annual performance bonuses and flexible health/fitness stipends.
• Profound work-from-home remote autonomy with flexible hours and a 1-month work-from-anywhere global allowance each year.
• Direct enrollment options into our corporate **Employee Share Ownership Plan (ESOP)** to share in our upcoming public listing trajectory.
• A progressive, highly kind startup culture built on structured thinking, absolute transparency, and collaborative personal development support.