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Open nowPosted 15 days ago

Data Engineer

Workable (global search)109,826 open roles

Where
Kondapur, TS, India
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Your applicationOpen nowData EngineerWorkable (global search) · Kondapur, TS, India

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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 2 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 15 days ago

Workable (global search) median: 2 days open

The posting

Coretek is looking for a Data Engineer to build and operate the pipelines and data models that the rest of the business runs on. You'll own ingestion from source systems through to curated, well-documented datasets that analysts, data scientists, and application teams depend on. This is a hands-on engineering role: you'll write production code, design schemas, and be accountable for the reliability and cost of what you ship.

Responsibilities

  • Design, build, and maintain batch and streaming data pipelines that are idempotent, observable, and recoverable.
  • Model data for analytics (dimensional models, semantic layers, and curated marts), balancing query performance against maintainability.
  • Integrate data from operational databases, SaaS APIs, files, and event streams, including handling schema drift and late-arriving data.
  • Build data quality checks (freshness, volume, uniqueness, referential integrity) into pipelines rather than bolting them on afterward, and define how failures alert and escalate.
  • Own pipelines in production: monitoring, on-call rotation for data incidents, root-cause analysis, and backfills.
  • Tune performance and cost (partitioning, clustering, file sizing, warehouse and cluster sizing) and make the tradeoffs explicit.
  • Apply engineering discipline to data: version control, code review, CI/CD, automated testing, and infrastructure as code.
  • Implement access controls, PII handling, retention, and lineage and audit requirements in partnership with security and compliance.
  • Partner with analysts, data scientists, and product engineers to turn ambiguous requirements into durable data contracts.
  • Maintain data dictionaries, lineage, and pipeline runbooks so consumers can find a dataset, understand what each field means and how current it is, and use it correctly without having to ask the team that built it.

Requirements

  • 5+ years building production data pipelines.
  • Strong hands-on Python development for data engineering, with real testing, packaging, and code review practice, not scripting alone.
  • Working knowledge of PySpark: DataFrame and SQL APIs, joins and aggregations at scale, partitioning and shuffle behavior, and the ability to read a Spark UI to diagnose a slow or failing job.
  • Strong SQL: window functions, query plans, and performance tuning, not just SELECTs.
  • Hands-on experience with the Azure data platform: Data Factory, Databricks, Synapse/Fabric, and ADLS.
  • Solid data modeling fundamentals: normalization, star schemas, slowly changing dimensions.
  • Git-based workflow and experience shipping through CI/CD.
  • Excellent communication skills, with the ability to debug a failing pipeline end to end and articulate the impact to diverse audiences, including non-technical stakeholders.
  • Exceptional analytical and problem-solving skills, with the judgment to find the root cause of a data issue rather than patching the symptom.
  • Strong knowledge and experience in working with customers in a consultative approach in a technical environment.

Additional Qualifications

  • Streaming experience (Kafka, Event Hubs).
  • Lakehouse formats: Delta Lake, Iceberg.
  • Infrastructure as code (Terraform, Bicep) and containerization (Docker, Kubernetes).
  • Experience in a regulated environment (HIPAA, SOC 2, PCI, GDPR): auditability, encryption, data residency.
  • Experience building data platforms for ML or supporting feature pipelines.
  • Proven ability to manage multiple client projects and deliver high-quality results on time.
  • Experience in Azure DevOps or GitHub for source control and pipelines.
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