W Code - Pattern-Based DSA Learning Platform

Bhanu Bisht

Dashboard RoadmapsData Engineer

🔧

Data Engineer

Design and build data pipelines that ingest, transform, and deliver reliable data at scale.

Demand

Very High

India Salary

₹6L – ₹35L

Global Salary

$80K – $170K

Math

Low+

Coding

High

Remote

★★★★★

What You Actually Do Daily

Design and build data pipelines that ingest, transform, and load data reliably

Architect data warehouses and data lakehouse solutions for analytics workloads

Build and maintain real-time streaming pipelines (Kafka + Flink/Spark Streaming)

Implement data quality frameworks: Great Expectations, Soda, dbt tests

Manage metadata catalogues, data lineage tracking, and documentation

Optimize query performance in BigQuery / Snowflake / Redshift for cost and speed

Collaborate with data analysts and ML engineers as the primary data supplier

Skills You Need

Python: PySpark, Pandas, production-grade pipeline scripting

SQL: expert level + warehouse-specific syntax (BigQuery, Snowflake, or Redshift)

Batch processing: Apache Spark (PySpark) — the single most critical tool

Stream processing: Apache Kafka + Spark Streaming or Apache Flink

Orchestration: Apache Airflow (mandatory), Prefect (growing), Dagster (rising)

Data transformation: dbt — know it deeply, not just basics

Cloud data stack: BigQuery (GCP), Redshift (AWS), or Snowflake

Tools & Technologies

Apache Spark (PySpark)

Large-scale batch data processing

Apache Kafka

Real-time event streaming

Apache Airflow / Prefect

Pipeline workflow orchestration

dbt (data build tool)

SQL-based data transformation

BigQuery / Snowflake

Cloud data warehouse

Delta Lake / Apache Iceberg

Open table format for lakehouse

Terraform

Infrastructure for data platform

Great Expectations

Data quality and validation

Fundamentals (Non-Negotiable)

OLTP vs OLAP: design differences and when to use each architecture

Star schema and snowflake schema: dimensional modeling and denormalization

Slowly Changing Dimensions (SCD Type 1, 2, 3) — standard interview topic

CAP theorem applied to distributed data storage systems

Partitioning, clustering, and query optimization in columnar data stores

Learning Roadmap

0–3 Months— SQL + Python Pipelines

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SQL mastery: advanced queries on BigQuery free tier (100GB/month free)

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Python + Pandas: 10 real ETL scripts (CSV/JSON/API → transform → write to database)

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Airflow: deploy via Docker Compose; build 5 real DAGs with dependencies and retries

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dbt: complete free dbt Fundamentals course; model a star schema from raw tables

3–6 Months— Big Data Stack

▸

PySpark: set up via Docker; process 1GB+ dataset; window functions and aggregations

▸

Kafka: producer-consumer basics; build a real-time event pipeline simulation

▸

dbt Advanced: tests, macros, incremental models, documentation generation

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Complete batch pipeline: API → raw layer → dbt transform → analytics-ready layer

6–12 Months— Lakehouse + Streaming

▸

Delta Lake / Apache Iceberg: implement a lakehouse architecture on S3 or GCS

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Real-time pipeline: Kafka + Spark Streaming → Delta table → dashboard

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Data quality: Great Expectations implementation with auto-failure alerts

▸

Apply for Data Engineer roles at e-commerce, fintech, healthtech companies

1–2 Years— Advanced Streaming + Governance

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Apache Flink: growing demand for sub-second latency streaming systems

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Data governance: Apache Atlas, Unity Catalog (Databricks)

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Databricks Certified Associate Developer certification

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Target Senior Data Engineer at product companies: Swiggy, Razorpay, Zepto, CRED

Salary Breakdown

Level	India	Global	Note
Junior / 0–2 yr	₹6L – ₹12L	$50K – $85K	SQL + Airflow + dbt skills
Mid-level / 3–5 yr	₹12L – ₹25L	$85K – $130K	Spark + streaming pipeline owner
Senior / 5+ yr	₹25L – ₹35L	$130K – $170K	Data Platform Lead or Principal DE

Portfolio Projects

End-to-End Lakehouse

Advanced

S3 + Delta Lake + dbt + Airflow + Superset

Delta LakedbtAirflowS3

Real-Time Analytics Pipeline

Advanced

Kafka + Spark Streaming

KafkaSparkDelta Lake

Data Quality Framework

Intermediate

Automated quality checks + alerting

Great ExpectationsAirflowSlack

Dimensional Data Model

Intermediate

Star schema for e-commerce in dbt

dbtBigQueryLooker

Certifications

dbt Fundamentals

dbt Labs · Free

Industry standard data transformation

Databricks Spark Developer

Databricks · Paid (~$200)

Gold standard for big data processing

Google Professional Data Engineer

Google · Paid (~$200)

End-to-end GCP data platform cert

Snowflake SnowPro Core

Snowflake · Paid (~$175)

Remote Work Viability

★★★★★5/5 Remote Friendliness

Very high remote potential. European and US data teams regularly hire Indian engineers. dbt project on GitHub + Airflow DAGs + deployed pipeline = strong application.

Arc.devTuring.comWellfoundLinkedIn

Freelancing Potential

$60 – $150/hr

High scope. Data pipeline setup, cloud warehouse migration, dbt project builds.

UpworkToptal

Common Mistakes to Avoid

SQL-only data engineering without Spark — will hit ceiling immediately at scale

Not learning dbt — it is now an industry standard in modern data stack companies

Pipelines without data quality checks — #1 production data failure mode

5-Year Outlook

Excellent. Every company building data products needs reliable data engineering. Streaming expertise + LLM data pipelines (training data curation, vector pipeline management) = premium profile.