Principal Data Engineer

Overview

Through proprietary software and AI, Sleek makes the back-office easy for micro SMEs and focuses on customer delight. We give Entrepreneurs time back to focus on growing their business and being with customers. With a surging number of Entrepreneurs globally, we are innovating in a highly lucrative space. We operate 3 business segments: Corporate Secretary, Accounting & Bookkeeping, and FinTech payments. Sleek launched in 2017 and now has around 15,000 customers across offices in Singapore, Hong Kong, Australia and the UK, with around 500 staff maintaining an intact startup mindset. We are backed by world-class investors and on track to be cash flow positive, tech-enabled, unicorns based in Singapore.

We are looking for a Principal Data Engineer who is excited about the mission and outcomes described below for the next 6-12 months.

Mission

Mission: Work closely with cross-functional teams to translate our business vision into impactful data solutions. Drive the alignment of data architecture requirements with strategic goals, ensuring each solution meets analytical needs and advances core objectives. Bridge business insights and technical execution by tackling complex data integration, modeling, and security challenges, and set the stage for exceptional data performance and insights. Shape the data roadmap, influence design decisions, and empower the team to deliver innovative, scalable, high-quality data solutions every day.

Outcomes

1. Architecture & Design:
   • Define the overall greenfield data architecture (batch + streaming) using GCP - BigQuery.
   • Establish best practices for ingestion, transformation, data quality, and governance.
2. Data Ingestion & Processing:
   • Lead the design and implementation of ETL/ELT pipelines.
   • Ingestion: Datastream, Pub/Sub, Dataflow, Airbyte, Fivetran, Rivery
   • Storage & Compute: BigQuery, GCS
   • Transformations: dbt, Cloud Composer (Airflow), Dagster
   • Ensure data quality and reliability with dbt tests, Great Expectations/Soda, and monitoring.
3. Governance & Security:
   • Implement Dataplex & Data Catalog for metadata, lineage, and discoverability.
   • Define IAM policies, row/column-level security, DLP strategies, and compliance controls.
4. Monitoring, Observability & Reliability:
   • Define and enforce SLAs, SLOs, and SLIs for pipelines and data products.
   • Implement observability tooling: Cloud-native options (Cloud Monitoring, Logging, Error Reporting, Cloud Trace).
   • Third-party (nice-to-have): Monte Carlo, Datafold, Databand, Bigeye.
   • Build alerting and incident response playbooks for data failures and anomalies.
   • Ensure pipeline resilience (idempotency, retries, backfills, incremental loads).
   • Establish disaster recovery and high availability strategies (multi-region storage, backup/restore policies).
5. Analytics Enablement:
   • Partner with BI/analytics teams to deliver governed self-service through Looker, Looker Studio, and other tools.
   • Support squad-level data product ownership with clear contracts and SLAs.
6. Team Leadership:
   • Mentor a small data engineering team; set coding, CI/CD, and operational standards.
   • Collaborate with squads, product managers, and leadership to deliver trusted data.

To do this you will have

• 10+ years experience in data engineering, architecture, or platform roles.
• Strong expertise in GCP data stack: BigQuery, GCS, Dataplex, Data Catalog, Pub/Sub, Dataflow.
• Hands-on experience building ETL/ELT pipelines with dbt + orchestration (Composer/Airflow/Dagster).
• Deep knowledge of data modeling, warehousing, partitioning/clustering strategies.
• Experience with monitoring, reliability engineering, and observability for data systems.
• Familiarity with data governance, lineage, and security policies (IAM, DLP, encryption).
• Strong SQL skills and solid knowledge of Python for data engineering.

Nice-to-Have

• Experience with Snowflake, Databricks, AWS (Redshift, Glue, Athena), or Azure Synapse.
• Knowledge of open-source catalogs (DataHub, Amundsen, OpenMetadata).
• Background in streaming systems (Kafka, Kinesis, Flink, Beam).
• Exposure to data observability tools (Monte Carlo, Bigeye, Datafold, Databand).
• Prior work with Looker, Hex, or other BI/analytics tools.
• Startup or scale-up experience (fast-moving, resource-constrained environments).

Behavioural fit

Behavioural fit is important at Sleek. We look for candidates with the following attributes in recent roles:

• Ownership: Reliability to see tasks through to completion and proactively address challenges.
• Humility: Openness to feedback and willingness to learn from others.
• Structured Thinking: Ability to balance needs of the organisation, team, and customers.
• Attention to detail: Managing multiple complex workstreams and noticing gaps.
• Excellent listener and clear communicator: Clear communication across diverse teams.

Interview process

The successful candidate will participate in the interview stages listed below. The order may vary by location and role. Process is expected to last no more than 3 weeks from start to finish.

• Screening call: ~30 minute chat with Talent Acquisition about you and your goals.
• Technical screening: ~30 minute call with a Senior Data Engineer to cover core skills.
• Technical competency panel: ~60 minute panel interview focusing on Python and SQL.
• Behavioural panel interview: ~60 minute conversation with business leaders.
• Final interview: Closing conversation with our CTO.
• Offer + references: Non-binding offer and reference checks.

Background checks

Sleek is a regulated entity and performs background checks based on role. This may include external verification of education, criminal history, political exposure, and bankruptcy/adverse credit history. Your consent will be obtained, and an adverse result may impact probation.

By applying, you confirm you have read and agree to our Data Privacy Statement for Candidates at sleek.com.

What we offer

• Humility and kindness : A culture of inclusion and respect.
• Flexibility : Work from home 5 days per week; fully remote from anywhere in the world for 1 month per year.
• Financial benefits : Competitive salaries, generous PTO, potential employee share ownership plan, and path toward IPO.
• Personal growth : Responsibility, autonomy, training, and exposure to AI in our regional AI center.
• Additional: Sleek is a certified B Corp with environmental initiatives and a carbon neutrality goal by 2030.

We are excited to grow with you at Sleek.

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